| Title: | Summary Scores of the Adolescent Brain Cognitive Development (ABCD) Study |
|---|---|
| Description: | Provides functions to compute summary scores (besides proprietary ones) reported in the tabulated data resource that is released by the Adolescent Brain Cognitive Development (ABCD) study. |
| Authors: | Le Zhang [aut, cre] (ORCID: <https://orcid.org/0009-0008-0205-2150>), Janosch Linkersdoerfer [aut] (ORCID: <https://orcid.org/0000-0002-1577-1233>), Olivier Celhay [aut] (ORCID: <https://orcid.org/0000-0002-2971-9110>), Biplabendu Das [aut] (ORCID: <https://orcid.org/0000-0003-0855-262X>), Sammy Berman [aut] (ORCID: <https://orcid.org/0000-0002-9803-019X>), Laura Ziemer [aut] (ORCID: <https://orcid.org/0000-0003-0026-3823>), Shermaine Abad [aut] (ORCID: <https://orcid.org/0009-0009-6013-9147>) |
| Maintainer: | Le Zhang <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 7.0.0 |
| Built: | 2026-05-16 00:16:34 UTC |
| Source: | https://github.com/cran/ABCDscores |
Checks the specified output column in a data frame and assigns NA to its
value depending on the missingness of a set of input columns.
If allow_missingness = TRUE, the output column is set to NA only when all
the specified input columns are NA.
If allow_missingness = FALSE, the output column is set to NA when any of
the input columns are NA.
This function is useful for propagating missingness from input variables
to a derived output.
check_assign_na(data, output, input, allow_missingness = TRUE)check_assign_na(data, output, input, allow_missingness = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
output |
character of length 1. The name of the first variable/column. |
input |
character. The name of the second variable/column. |
allow_missingness |
logical. Default set to TRUE. If TRUE, |
tbl. The input data frame with the output column modified.
# Example data dat <- tibble::tibble( a = c(1, NA, 3), b = c(NA, NA, 2), c = c(1, 2, 3), out = c(10, 11, 12) ) # Assign NA to out when all of a and b are NA check_assign_na( dat, output = "out", input = c("a", "b"), allow_missingness = TRUE ) # Assign NA to out when any of a and b are NA check_assign_na( dat, output = "out", input = c("a", "b"), allow_missingness = FALSE )# Example data dat <- tibble::tibble( a = c(1, NA, 3), b = c(NA, NA, 2), c = c(1, 2, 3), out = c(10, 11, 12) ) # Assign NA to out when all of a and b are NA check_assign_na( dat, output = "out", input = c("a", "b"), allow_missingness = TRUE ) # Assign NA to out when any of a and b are NA check_assign_na( dat, output = "out", input = c("a", "b"), allow_missingness = FALSE )
Takes a group of checkbox-style variables, have a common prefix and numeric suffixes representing options, and combines them into a single list column where each element is a vector of selected options (numbers).
This function expects the input data to include participant_id and
session_id columns, which are used to group responses. For each participant
and session, it collects all checkbox numbers that were selected as a single
list. The resulting column can be renamed via the name parameter.
combine_checkboxes(data, var_basename, var_sep = "___", name = NULL)combine_checkboxes(data, var_basename, var_sep = "___", name = NULL)
data |
tbl. Data frame containing the participant responses. |
var_basename |
character of length 1. The base name of the checkbox field. |
var_sep |
character of length 1. The string separating the base name
of the checkbox and the checkbox value. Default is |
name |
character of length 1 or |
tbl. The input data frame with an additional column containing a list of integers corresponding to the selected checkbox options for each participant and session.
# Example data dat <- tibble::tibble( participant_id = c(1, 1, 2), session_id = c(1, 2, 1), q1___1 = c(1, NA, 0), q1___2 = c(0, 1, 1), q1___3 = c(NA, NA, 0) ) # Combine q1 checkboxes into a single list column combine_checkboxes(dat, var_basename = "q1") # Combine and rename the output column combine_checkboxes(dat, var_basename = "q1", name = "q1_combined")# Example data dat <- tibble::tibble( participant_id = c(1, 1, 2), session_id = c(1, 2, 1), q1___1 = c(1, NA, 0), q1___2 = c(0, 1, 1), q1___3 = c(NA, NA, 0) ) # Combine q1 checkboxes into a single list column combine_checkboxes(dat, var_basename = "q1") # Combine and rename the output column combine_checkboxes(dat, var_basename = "q1", name = "q1_combined")
Combines two columns into one. The name of the first column is used for the new column, the second column is removed. Used for cases where different versions of the same variable exist that have to be combined before computing a summary score.
combine_cols(data, col_1, col_2, name = NULL, keep_other = TRUE)combine_cols(data, col_1, col_2, name = NULL, keep_other = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
col_1 |
character. The name of the first variable/column. |
col_2 |
character. The name of the second variable/column. |
name |
character. The name of the field with the combined data.
By default, |
keep_other |
logical. Whether to combine the combined column with the input data frame (Default: TRUE). |
tbl. The input data frame with the combined column and the second
column removed. The name of the combined column is the same as col_1,
or user-specified in the name argument.
data <- tibble::tibble( var_id = c("A", "B", "C"), var_orig = c(1, NA, 3), var_alt = c(NA, 2, 4) ) data |> combine_cols( col_1 = "var_orig", col_2 = "var_alt" ) data |> combine_cols( "var_orig", "var_alt", name = "out" ) data |> combine_cols( "var_orig", "var_alt", name = "out", keep_other = FALSE )data <- tibble::tibble( var_id = c("A", "B", "C"), var_orig = c(1, NA, 3), var_alt = c(NA, 2, 4) ) data |> combine_cols( col_1 = "var_orig", col_2 = "var_alt" ) data |> combine_cols( "var_orig", "var_alt", name = "out" ) data |> combine_cols( "var_orig", "var_alt", name = "out", keep_other = FALSE )
Combines levels from two columns into new level stored into a new column. Allows users to create new classifications using levels defined in existing fields.
combine_levels(data, vars, conds, default = NA, combine = TRUE)combine_levels(data, vars, conds, default = NA, combine = TRUE)
data |
tbl. Data frame containing the two columns to be summarized. |
vars |
named list of length 1. The name of the list component will be used as the name for the newly created variable/column, and the character elements specifies the two existing fields from which the levels will be combined. |
conds |
named list. The name of the each of the list element will be used as the label for the new level created, and the two character vectors represent the levels in the first and second variables, respectively, that will be combined to create the new level. |
default |
character (or |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the new column with combined levels appended at the end.
data <- tibble::tibble( var_1 = c("a", "b", "b", "c"), var_2 = c(1, NA, 2, 3) ) data |> combine_levels( vars = list( "var_3" = c("var_1", "var_2") ), conds = list( "a1" = list("a", 1), "b0" = list("b", NA), "b2" = list("b", 2) ), default = "var_1", combine = TRUE )data <- tibble::tibble( var_1 = c("a", "b", "b", "c"), var_2 = c(1, NA, 2, 3) ) data |> combine_levels( vars = list( "var_3" = c("var_1", "var_2") ), conds = list( "a1" = list("a", 1), "b0" = list("b", NA), "b2" = list("b", 2) ), default = "var_1", combine = TRUE )
Computes the summary score ab_g_dyn__cohort_income__hhold__3lvl
Cohort description: Household income - 3 levels
Summarized variables:
ab_p_demo__income__hhold_001
ab_p_demo__income__hhold_001__v01
compute_ab_g_dyn__cohort_income__hhold__3lvl( data, name = "ab_g_dyn__cohort_income__hhold__3lvl", combine = TRUE )compute_ab_g_dyn__cohort_income__hhold__3lvl( data, name = "ab_g_dyn__cohort_income__hhold__3lvl", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_ab_g_dyn__cohort_income__hhold__6lvl()
A single function to compute all scores in the above domain using default arguments.
compute_ab_g_dyn_all(data)compute_ab_g_dyn_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ab_g_dyn_all(data) ## End(Not run)## Not run: compute_ab_g_dyn_all(data) ## End(Not run)
A single function to compute all scores in the above domain using default arguments.
compute_ab_g_stc_all(data)compute_ab_g_stc_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ab_g_stc_all(data) ## End(Not run)## Not run: compute_ab_g_stc_all(data) ## End(Not run)
A single function to compute all scores in the above domain using default arguments.
compute_ab_p_demo__ntvam_all(data)compute_ab_p_demo__ntvam_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
Calculate the time difference between two dates in specified units (years, months, or days). Uses lubridate intervals for accurate calculations across calendar irregularities.
compute_age(date_start, date_end, unit = c("years", "months", "days"))compute_age(date_start, date_end, unit = c("years", "months", "days"))
date_start |
Starting date. Must be a date or datetime object compatible with lubridate. |
date_end |
Ending date. Must be a date or datetime object compatible with lubridate. |
unit |
Character string specifying the unit for the result. Must be one of "years", "months", or "days". Defaults to "years". |
A numeric value representing the time difference in the specified unit.
# Calculate age in years compute_age(as.Date("1990-01-01"), as.Date("2024-01-01")) # Calculate age in months compute_age(as.Date("2023-01-01"), as.Date("2024-01-01"), unit = "months") # Calculate age in days compute_age(as.Date("2023-12-01"), as.Date("2024-01-01"), unit = "days")# Calculate age in years compute_age(as.Date("1990-01-01"), as.Date("2024-01-01")) # Calculate age in months compute_age(as.Date("2023-01-01"), as.Date("2024-01-01"), unit = "months") # Calculate age in days compute_age(as.Date("2023-12-01"), as.Date("2024-01-01"), unit = "days")
Computes a binary endorsement indicator, for alcohol or drug use
computed using a set of variables.
Resulting indicator is either 0 (FALSE) or 1 (TRUE), and
NA for missing or non-responses (777, 888, or 999).
Notes:
Following values are recoded as NA prior to any computation
777
888
999
compute_famhx_endorsement(data, name, var_matches, combine = TRUE)compute_famhx_endorsement(data, name, var_matches, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
var_matches |
character of length one. The base name of the checkbox
field that is used to find all corresponding columns in |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
A tibble with the computed score for each participant/event.
## Not run: compute_famhx_endorsement( data = data, name = "mh_p_famhx__alc__fath_indicator", var_matches = "mh_p_famhx__alc__fath_001" ) ## End(Not run)## Not run: compute_famhx_endorsement( data = data, name = "mh_p_famhx__alc__fath_indicator", var_matches = "mh_p_famhx__alc__fath_001" ) ## End(Not run)
Computes the summary score fc_p_fes__cohes_nm
(Family Environment Scale [Parent] (Cohesion): Number missing)
Summarized variables:
fc_p_fes__cohes_001
fc_p_fes__cohes_002
fc_p_fes__cohes_003
fc_p_fes__cohes_004
fc_p_fes__cohes_005
fc_p_fes__cohes_006
fc_p_fes__cohes_007
fc_p_fes__cohes_008
fc_p_fes__cohes_009
Excluded values:
777
999
compute_fc_p_fes__cohes_nm( data, name = "fc_p_fes__cohes_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__cohes_nm( data, name = "fc_p_fes__cohes_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_fes__cohes_mean()
Computes the summary score fc_p_fes__confl_nm
(Family Environment Scale [Parent] (Conflict): Number missing)
Summarized variables:
fc_p_fes__confl_001
fc_p_fes__confl_002
fc_p_fes__confl_003
fc_p_fes__confl_004
fc_p_fes__confl_005
fc_p_fes__confl_006
fc_p_fes__confl_007
fc_p_fes__confl_008
fc_p_fes__confl_009
Excluded values:
777
999
compute_fc_p_fes__confl_nm( data, name = "fc_p_fes__confl_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__confl_nm( data, name = "fc_p_fes__confl_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_fes__confl_mean()
Computes the summary score fc_p_fes__expr_nm
(Family Environment Scale [Parent] (Expression): Number missing)
Summarized variables:
fc_p_fes__expr_001
fc_p_fes__expr_002
fc_p_fes__expr_003
fc_p_fes__expr_004
fc_p_fes__expr_005
fc_p_fes__expr_006
fc_p_fes__expr_007
fc_p_fes__expr_008
fc_p_fes__expr_009
Excluded values:
777
999
compute_fc_p_fes__expr_nm( data, name = "fc_p_fes__expr_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__expr_nm( data, name = "fc_p_fes__expr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__intelcult_nm
(Family Environment Scale [Parent] (Intellectual and cultural): Number
missing)
Summarized variables:
fc_p_fes__intelcult_001
fc_p_fes__intelcult_002
fc_p_fes__intelcult_003
fc_p_fes__intelcult_004
fc_p_fes__intelcult_005
fc_p_fes__intelcult_006
fc_p_fes__intelcult_007
fc_p_fes__intelcult_008
fc_p_fes__intelcult_009
Excluded values:
777
999
compute_fc_p_fes__intelcult_nm( data, name = "fc_p_fes__intelcult_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__intelcult_nm( data, name = "fc_p_fes__intelcult_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_fes__intelcult_mean()
Computes the summary score fc_p_fes__org_nm
(Family Environment Scale [Parent] (Organization): Number missing)
Summarized variables:
fc_p_fes__org_001
fc_p_fes__org_002
fc_p_fes__org_003
fc_p_fes__org_004
fc_p_fes__org_005
fc_p_fes__org_006
fc_p_fes__org_007
fc_p_fes__org_008
fc_p_fes__org_009
Excluded values:
777
999
compute_fc_p_fes__org_nm( data, name = "fc_p_fes__org_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__org_nm( data, name = "fc_p_fes__org_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__rec_nm
(Family Environment Scale [Parent] (Activity and recreational): Number
missing)
Summarized variables:
fc_p_fes__rec_001
fc_p_fes__rec_002
fc_p_fes__rec_003
fc_p_fes__rec_004
fc_p_fes__rec_005
fc_p_fes__rec_006
fc_p_fes__rec_007
fc_p_fes__rec_008
fc_p_fes__rec_009
Excluded values:
777
999
compute_fc_p_fes__rec_nm( data, name = "fc_p_fes__rec_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_fes__rec_nm( data, name = "fc_p_fes__rec_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_fes_all(data)compute_fc_p_fes_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_fes_all(data) ## End(Not run)## Not run: compute_fc_p_fes_all(data) ## End(Not run)
Computes the summary score fc_p_meim__commattach_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and
attachment): Number missing)
Summarized variables:
fc_p_meim__commattach_001
fc_p_meim__commattach_002
fc_p_meim__commattach_003
Excluded values: none
compute_fc_p_meim__commattach_nm( data, name = "fc_p_meim__commattach_nm", combine = TRUE )compute_fc_p_meim__commattach_nm( data, name = "fc_p_meim__commattach_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_meim__commattach_mean()
Computes the summary score fc_p_meim__explor_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration):
Number missing)
Summarized variables:
fc_p_meim__explor_001
fc_p_meim__explor_002
fc_p_meim__explor_003
Excluded values: none
compute_fc_p_meim__explor_nm( data, name = "fc_p_meim__explor_nm", combine = TRUE )compute_fc_p_meim__explor_nm( data, name = "fc_p_meim__explor_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_meim__explor_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_meim_all(data)compute_fc_p_meim_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_meim_all(data) ## End(Not run)## Not run: compute_fc_p_meim_all(data) ## End(Not run)
Computes the summary score fc_p_meim_nm
(The Multigroup Ethnic Identity Measure-Revised [Parent]: Number missing)
Summarized variables:
fc_p_meim__commattach_001
fc_p_meim__commattach_002
fc_p_meim__commattach_003
fc_p_meim__explor_001
fc_p_meim__explor_002
fc_p_meim__explor_003
Excluded values: none
compute_fc_p_meim_nm(data, name = "fc_p_meim_nm", combine = TRUE)compute_fc_p_meim_nm(data, name = "fc_p_meim_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nce__cc_nm
(Neighborhood Collective Efficacy [Parent] (Community cohesion): Number
missing)
Summarized variables:
fc_p_nce__cc_001
fc_p_nce__cc_002
fc_p_nce__cc_003
fc_p_nce__cc_004
fc_p_nce__cc_005
Excluded values:
777
compute_fc_p_nce__cc_nm(data, name = "fc_p_nce__cc_nm", combine = TRUE)compute_fc_p_nce__cc_nm(data, name = "fc_p_nce__cc_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nce__isc_nm
(Neighborhood Collective Efficacy [Parent] (Informal social control): Number
missing)
Summarized variables:
fc_p_nce__isc_001
fc_p_nce__isc_002
fc_p_nce__isc_003
fc_p_nce__isc_004
fc_p_nce__isc_005
Excluded values:
777
compute_fc_p_nce__isc_nm(data, name = "fc_p_nce__isc_nm", combine = TRUE)compute_fc_p_nce__isc_nm(data, name = "fc_p_nce__isc_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_nce_all(data)compute_fc_p_nce_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_nce_all(data) ## End(Not run)## Not run: compute_fc_p_nce_all(data) ## End(Not run)
Computes the summary score fc_p_nce_nm
(Neighborhood Collective Efficacy [Parent]: Number missing)
Summarized variables:
fc_p_nce__cc_001
fc_p_nce__cc_002
fc_p_nce__cc_003
fc_p_nce__cc_004
fc_p_nce__cc_005
fc_p_nce__isc_001
fc_p_nce__isc_002
fc_p_nce__isc_003
fc_p_nce__isc_004
fc_p_nce__isc_005
Excluded values:
777
compute_fc_p_nce_nm(data, name = "fc_p_nce_nm", combine = TRUE)compute_fc_p_nce_nm(data, name = "fc_p_nce_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nsc__ns_nm
(Neighborhood Safety & Crime [Parent] (Neighborhood safety): Number missing)
Summarized variables:
fc_p_nsc__ns_001
fc_p_nsc__ns_002
fc_p_nsc__ns_003
Excluded values:
777
999
compute_fc_p_nsc__ns_nm(data, name = "fc_p_nsc__ns_nm", combine = TRUE)compute_fc_p_nsc__ns_nm(data, name = "fc_p_nsc__ns_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_nsc_all(data)compute_fc_p_nsc_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_nsc_all(data) ## End(Not run)## Not run: compute_fc_p_nsc_all(data) ## End(Not run)
Computes the summary score fc_p_pk__knowl_nm
(Parental Knowledge Scale [Parent]: Number missing)
Summarized variables:
fc_p_pk__knowl_001
fc_p_pk__knowl_002
fc_p_pk__knowl_003
fc_p_pk__knowl_004
fc_p_pk__knowl_005
fc_p_pk__knowl_006
fc_p_pk__knowl_007
fc_p_pk__knowl_008
fc_p_pk__knowl_009
Excluded values:
777
compute_fc_p_pk__knowl_nm(data, name = "fc_p_pk__knowl_nm", combine = TRUE)compute_fc_p_pk__knowl_nm(data, name = "fc_p_pk__knowl_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_pk_all(data)compute_fc_p_pk_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_pk_all(data) ## End(Not run)## Not run: compute_fc_p_pk_all(data) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_psb_all(data)compute_fc_p_psb_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_psb_all(data) ## End(Not run)## Not run: compute_fc_p_psb_all(data) ## End(Not run)
Computes the summary score fc_p_psb_nm
(Prosocial Behavior [Parent]: Number missing)
Summarized variables:
fc_p_psb_001
fc_p_psb_002
fc_p_psb_003
Excluded values:
777
999
compute_fc_p_psb_nm( data, name = "fc_p_psb_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_psb_nm( data, name = "fc_p_psb_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__famil_nm__v01
(Values Scale [Parent] (Familism): Number missing (Subscales: supp, ref, obl))
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
fc_p_vs__obl_001
fc_p_vs__obl_002
fc_p_vs__obl_003
fc_p_vs__obl_004
fc_p_vs__obl_005
Excluded values:
777
999
compute_fc_p_vs__famil_nm( data, name = "fc_p_vs__famil_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__famil_nm( data, name = "fc_p_vs__famil_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__famil_nm__v01
(Values Scale [Parent] (Familism): Number missing - Version 1
(Year 5 onwards))
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
Excluded values:
777
999
compute_fc_p_vs__famil_nm__v01( data, name = "fc_p_vs__famil_nm__v01", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__famil_nm__v01( data, name = "fc_p_vs__famil_nm__v01", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_vs__famil_mean__v01()
Computes the summary score fc_p_vs__indselfrel_nm
(Values Scale [Parent] (Independence and
self-reliance): Number missing)
Summarized variables:
fc_p_vs__indselfrel_001
fc_p_vs__indselfrel_002
fc_p_vs__indselfrel_003
fc_p_vs__indselfrel_004
fc_p_vs__indselfrel_005
Excluded values:
777
999
compute_fc_p_vs__indselfrel_nm( data, name = "fc_p_vs__indselfrel_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__indselfrel_nm( data, name = "fc_p_vs__indselfrel_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_p_vs__indselfrel_mean()
Computes the summary score fc_p_vs__obl_nm
(Values Scale [Parent] (Family obligation): Number
missing)
Summarized variables:
fc_p_vs__obl_001
fc_p_vs__obl_002
fc_p_vs__obl_003
fc_p_vs__obl_004
fc_p_vs__obl_005
Excluded values:
777
999
compute_fc_p_vs__obl_nm( data, name = "fc_p_vs__obl_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__obl_nm( data, name = "fc_p_vs__obl_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__ref_nm
(Values Scale [Parent] (Family as referent): Number
missing)
Summarized variables:
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
Excluded values:
777
999
compute_fc_p_vs__ref_nm( data, name = "fc_p_vs__ref_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__ref_nm( data, name = "fc_p_vs__ref_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__relig_nm
(Values Scale [Parent] (Religion): Number missing)
Summarized variables:
fc_p_vs__relig_001
fc_p_vs__relig_002
fc_p_vs__relig_003
fc_p_vs__relig_004
fc_p_vs__relig_005
fc_p_vs__relig_006
fc_p_vs__relig_007
Excluded values:
777
999
compute_fc_p_vs__relig_nm( data, name = "fc_p_vs__relig_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__relig_nm( data, name = "fc_p_vs__relig_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__supp_nm
(Values Scale [Parent] (Family support): Number
missing)
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
Excluded values:
777
999
compute_fc_p_vs__supp_nm( data, name = "fc_p_vs__supp_nm", exclude = c("777", "999"), combine = TRUE )compute_fc_p_vs__supp_nm( data, name = "fc_p_vs__supp_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_p_vs_all(data)compute_fc_p_vs_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_p_vs_all(data) ## End(Not run)## Not run: compute_fc_p_vs_all(data) ## End(Not run)
Computes the summary score fc_y_as__safe_nm
(Activity Space [Youth] (Safety): Number missing)
Summarized variables:
fc_y_as__safe_001a
fc_y_as__safe_001b
fc_y_as__safe_001c
Excluded values: none
compute_fc_y_as__safe_nm(data, name = "fc_y_as__safe_nm", combine = TRUE)compute_fc_y_as__safe_nm(data, name = "fc_y_as__safe_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_as_all(data)compute_fc_y_as_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_as_all(data) ## End(Not run)## Not run: compute_fc_y_as_all(data) ## End(Not run)
Computes the summary score fc_y_crpbi__cg1_nm
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A):
Number missing)
Summarized variables:
fc_y_crpbi__cg1_002
fc_y_crpbi__cg1_003
fc_y_crpbi__cg1_004
fc_y_crpbi__cg1_005
fc_y_crpbi__cg1_006
Excluded values: none
compute_fc_y_crpbi__cg1_nm(data, name = "fc_y_crpbi__cg1_nm", combine = TRUE)compute_fc_y_crpbi__cg1_nm(data, name = "fc_y_crpbi__cg1_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_crpbi__cg1_mean()
Computes the summary score fc_y_crpbi__cg2_nm
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B):
Number missing)
Summarized variables:
fc_y_crpbi__cg2_002
fc_y_crpbi__cg2_003
fc_y_crpbi__cg2_004
fc_y_crpbi__cg2_005
fc_y_crpbi__cg2_006
Excluded values: none
compute_fc_y_crpbi__cg2_nm(data, name = "fc_y_crpbi__cg2_nm", combine = TRUE)compute_fc_y_crpbi__cg2_nm(data, name = "fc_y_crpbi__cg2_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_crpbi__cg2_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_crpbi_all(data)compute_fc_y_crpbi_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_crpbi_all(data) ## End(Not run)## Not run: compute_fc_y_crpbi_all(data) ## End(Not run)
Computes the summary score fc_y_eut__ethn_nm
(Experiences with Unfair Treatment [Youth] (Ethnicity): Number missing)
Summarized variables:
fc_y_eut__ethn_001a
fc_y_eut__ethn_001b
fc_y_eut__ethn_001c
fc_y_eut__ethn_001d
fc_y_eut__ethn_002
fc_y_eut__ethn_003a
fc_y_eut__ethn_003b
fc_y_eut__ethn_003c
Excluded values:
444
777
999
compute_fc_y_eut__ethn_nm(data, name = "fc_y_eut__ethn_nm", combine = TRUE)compute_fc_y_eut__ethn_nm(data, name = "fc_y_eut__ethn_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_eut_all(data)compute_fc_y_eut_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_eut_all(data) ## End(Not run)## Not run: compute_fc_y_eut_all(data) ## End(Not run)
Computes the summary score fc_y_fes__cohes_nm
(Family Environment Scale [Youth] (Cohesion): Number missing)
Summarized variables:
fc_y_fes__cohes_001
fc_y_fes__cohes_002
fc_y_fes__cohes_003
fc_y_fes__cohes_004
fc_y_fes__cohes_005
fc_y_fes__cohes_006
fc_y_fes__cohes_007
fc_y_fes__cohes_008
fc_y_fes__cohes_009
Excluded values:
777
compute_fc_y_fes__cohes_nm( data, name = "fc_y_fes__cohes_nm", exclude = c("777"), combine = TRUE )compute_fc_y_fes__cohes_nm( data, name = "fc_y_fes__cohes_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_fes__cohes_mean()
Computes the summary score fc_y_fes__confl_nm
(Family Environment Scale [Youth] (Conflict): Number missing)
Summarized variables:
fc_y_fes__confl_001
fc_y_fes__confl_002
fc_y_fes__confl_003
fc_y_fes__confl_004
fc_y_fes__confl_005
fc_y_fes__confl_006
fc_y_fes__confl_007
fc_y_fes__confl_008
fc_y_fes__confl_009
Excluded values:
777
compute_fc_y_fes__confl_nm( data, name = "fc_y_fes__confl_nm", exclude = c("777"), combine = TRUE )compute_fc_y_fes__confl_nm( data, name = "fc_y_fes__confl_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_fes__confl_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_fes_all(data)compute_fc_y_fes_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_fes_all(data) ## End(Not run)## Not run: compute_fc_y_fes_all(data) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_lone_all(data)compute_fc_y_lone_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_lone_all(data) ## End(Not run)## Not run: compute_fc_y_lone_all(data) ## End(Not run)
Computes the summary score fc_y_lone_nm
(UCLA Loneliness Scale [Youth]: Number missing)
Summarized variables:
fc_y_lone_001
fc_y_lone_002
fc_y_lone_003
fc_y_lone_004
fc_y_lone_005
fc_y_lone_006
fc_y_lone_007
Excluded values:
777
999
compute_fc_y_lone_nm(data, name = "fc_y_lone_nm", combine = TRUE)compute_fc_y_lone_nm(data, name = "fc_y_lone_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_meim__commattach_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and
attachment): Number missing)
Summarized variables:
fc_y_meim__commattach_001
fc_y_meim__commattach_002
fc_y_meim__commattach_003
Excluded values: none
compute_fc_y_meim__commattach_nm( data, name = "fc_y_meim__commattach_nm", combine = TRUE )compute_fc_y_meim__commattach_nm( data, name = "fc_y_meim__commattach_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_meim__commattach_mean()
Computes the summary score fc_y_meim__explor_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration):
Number missing)
Summarized variables:
fc_y_meim__explor_001
fc_y_meim__explor_002
fc_y_meim__explor_003
Excluded values: none
compute_fc_y_meim__explor_nm( data, name = "fc_y_meim__explor_nm", combine = TRUE )compute_fc_y_meim__explor_nm( data, name = "fc_y_meim__explor_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_meim__explor_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_meim_all(data)compute_fc_y_meim_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_meim_all(data) ## End(Not run)## Not run: compute_fc_y_meim_all(data) ## End(Not run)
Computes the summary score fc_y_meim_nm
(The Multigroup Ethnic Identity Measure-Revised [Youth]: Number missing)
Summarized variables:
fc_y_meim__commattach_001
fc_y_meim__commattach_002
fc_y_meim__commattach_003
fc_y_meim__explor_001
fc_y_meim__explor_002
fc_y_meim__explor_003
Excluded values: none
compute_fc_y_meim_nm(data, name = "fc_y_meim_nm", combine = TRUE)compute_fc_y_meim_nm(data, name = "fc_y_meim_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_mnbs__edusupp_nm
(Multidimensional Neglectful Behavior Scale [Youth] (Education support):
Number missing)
Summarized variables:
fc_y_mnbs__edusupp_001
fc_y_mnbs__edusupp_002
fc_y_mnbs__edusupp_003
Excluded values:
777
compute_fc_y_mnbs__edusupp_nm( data, name = "fc_y_mnbs__edusupp_nm", combine = TRUE )compute_fc_y_mnbs__edusupp_nm( data, name = "fc_y_mnbs__edusupp_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_mnbs__edusupp_mean()
Computes the summary score fc_y_mnbs__superv_nm
(Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Number
missing)
Summarized variables:
fc_y_mnbs__superv_001
fc_y_mnbs__superv_002
fc_y_mnbs__superv_003
fc_y_mnbs__superv_004
fc_y_mnbs__superv_005
Excluded values:
777
compute_fc_y_mnbs__superv_nm( data, name = "fc_y_mnbs__superv_nm", combine = TRUE )compute_fc_y_mnbs__superv_nm( data, name = "fc_y_mnbs__superv_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_mnbs__superv_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_mnbs_all(data)compute_fc_y_mnbs_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_mnbs_all(data) ## End(Not run)## Not run: compute_fc_y_mnbs_all(data) ## End(Not run)
Computes the summary score fc_y_mnbs_nm
(Multidimensional Neglectful Behavior Scale [Youth]: Number missing)
Summarized variables:
fc_y_mnbs__edusupp_001
fc_y_mnbs__edusupp_002
fc_y_mnbs__edusupp_003
fc_y_mnbs__superv_001
fc_y_mnbs__superv_002
fc_y_mnbs__superv_003
fc_y_mnbs__superv_004
fc_y_mnbs__superv_005
Excluded values:
777
compute_fc_y_mnbs_nm(data, name = "fc_y_mnbs_nm", combine = TRUE)compute_fc_y_mnbs_nm(data, name = "fc_y_mnbs_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
A single function to compute all scores in the above domain using default arguments.
compute_fc_y_naa_all(data)compute_fc_y_naa_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_pm_all(data)compute_fc_y_pm_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_pm_all(data) ## End(Not run)## Not run: compute_fc_y_pm_all(data) ## End(Not run)
Computes the summary score fc_y_pm_nm
(Parental Monitoring [Youth]: Number missing)
Summarized variables:
fc_y_pm_001
fc_y_pm_002
fc_y_pm_003
fc_y_pm_004
fc_y_pm_005
Excluded values:
777
compute_fc_y_pm_nm(data, name = "fc_y_pm_nm", combine = TRUE)compute_fc_y_pm_nm(data, name = "fc_y_pm_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_pnh_all(data)compute_fc_y_pnh_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_pnh_all(data) ## End(Not run)## Not run: compute_fc_y_pnh_all(data) ## End(Not run)
Computes the summary score fc_y_pnh_nm
(Peer Network Health [Youth]: Number missing)
Summarized variables:
fc_y_pnh_001
fc_y_pnh_002
fc_y_pnh_002__01
fc_y_pnh_003
fc_y_pnh_003__01
Excluded values:
777
compute_fc_y_pnh_nm( data, name = "fc_y_pnh_nm", exclude = c("777"), combine = TRUE )compute_fc_y_pnh_nm( data, name = "fc_y_pnh_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_psb_all(data)compute_fc_y_psb_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_psb_all(data) ## End(Not run)## Not run: compute_fc_y_psb_all(data) ## End(Not run)
Computes the summary score fc_y_psb_nm
(Prosocial Behavior [Youth]: Number missing)
Summarized variables:
fc_y_psb_001
fc_y_psb_002
fc_y_psb_003
Excluded values:
777
compute_fc_y_psb_nm( data, name = "fc_y_psb_nm", exclude = c("777"), combine = TRUE )compute_fc_y_psb_nm( data, name = "fc_y_psb_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_rpi_all(data)compute_fc_y_rpi_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_rpi_all(data) ## End(Not run)## Not run: compute_fc_y_rpi_all(data) ## End(Not run)
Computes the summary score fc_y_rpi_nm
(Resistance to Peer Influence [Youth]: Number missing)
Summarized variables:
fc_y_rpi_001
fc_y_rpi_002
fc_y_rpi_003
fc_y_rpi_004
fc_y_rpi_005
fc_y_rpi_006
fc_y_rpi_007
fc_y_rpi_008
fc_y_rpi_009
fc_y_rpi_010
Excluded values: none
compute_fc_y_rpi_nm(data, name = "fc_y_rpi_nm", combine = TRUE)compute_fc_y_rpi_nm(data, name = "fc_y_rpi_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__dis_nm
(School Risk & Protective Factors [Youth] (School disengagement): Number
missing)
Summarized variables:
fc_y_srpf__dis_001
fc_y_srpf__dis_002
Excluded values:
777
compute_fc_y_srpf__dis_nm( data, name = "fc_y_srpf__dis_nm", exclude = c("777"), combine = TRUE )compute_fc_y_srpf__dis_nm( data, name = "fc_y_srpf__dis_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__env_nm
(School Risk & Protective Factors [Youth] (School environment): Number
missing)
Summarized variables:
fc_y_srpf__env_001
fc_y_srpf__env_002
fc_y_srpf__env_003
fc_y_srpf__env_004
fc_y_srpf__env_005
fc_y_srpf__env_006
Excluded values:
777
compute_fc_y_srpf__env_nm( data, name = "fc_y_srpf__env_nm", exclude = c("777"), combine = TRUE )compute_fc_y_srpf__env_nm( data, name = "fc_y_srpf__env_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__involv_nm
(School Risk & Protective Factors [Youth] (School involvement): Number
missing)
Summarized variables:
fc_y_srpf__involv_001
fc_y_srpf__involv_002
fc_y_srpf__involv_003
fc_y_srpf__involv_004
Excluded values:
777
compute_fc_y_srpf__involv_nm( data, name = "fc_y_srpf__involv_nm", exclude = c("777"), combine = TRUE )compute_fc_y_srpf__involv_nm( data, name = "fc_y_srpf__involv_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_srpf__involv_mean()
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_srpf_all(data)compute_fc_y_srpf_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_srpf_all(data) ## End(Not run)## Not run: compute_fc_y_srpf_all(data) ## End(Not run)
Computes the summary score fc_y_vs__famil_nm__v01
(Values Scale [Youth] (Familism): Number missing (Subscales: supp, ref, obl))
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
fc_y_vs__obl_001
fc_y_vs__obl_002
fc_y_vs__obl_003
fc_y_vs__obl_004
fc_y_vs__obl_005
Excluded values:
777
compute_fc_y_vs__famil_nm( data, name = "fc_y_vs__famil_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__famil_nm( data, name = "fc_y_vs__famil_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__famil_nm__v01
(Values Scale [Youth] (Familism): Number missing - Version 1
(Year 5 onwards))
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
Excluded values:
777
compute_fc_y_vs__famil_nm__v01( data, name = "fc_y_vs__famil_nm__v01", exclude = c("777"), combine = TRUE )compute_fc_y_vs__famil_nm__v01( data, name = "fc_y_vs__famil_nm__v01", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_vs__famil_mean__v01()
Computes the summary score fc_y_vs__indselfrel_nm
(Values Scale [Youth] (Independence and
self-reliance): Number missing)
Summarized variables:
fc_y_vs__indselfrel_001
fc_y_vs__indselfrel_002
fc_y_vs__indselfrel_003
fc_y_vs__indselfrel_004
fc_y_vs__indselfrel_005
Excluded values:
777
compute_fc_y_vs__indselfrel_nm( data, name = "fc_y_vs__indselfrel_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__indselfrel_nm( data, name = "fc_y_vs__indselfrel_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_fc_y_vs__indselfrel_mean()
Computes the summary score fc_y_vs__obl_nm
(Values Scale [Youth] (Family obligation): Number
missing)
Summarized variables:
fc_y_vs__obl_001
fc_y_vs__obl_002
fc_y_vs__obl_003
fc_y_vs__obl_004
fc_y_vs__obl_005
Excluded values:
777
compute_fc_y_vs__obl_nm( data, name = "fc_y_vs__obl_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__obl_nm( data, name = "fc_y_vs__obl_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__ref_nm
(Values Scale [Youth] (Family as referent): Number
missing)
Summarized variables:
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
Excluded values:
777
compute_fc_y_vs__ref_nm( data, name = "fc_y_vs__ref_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__ref_nm( data, name = "fc_y_vs__ref_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__relig_nm
(Values Scale [Youth] (Religion): Number missing)
Summarized variables:
fc_y_vs__relig_001
fc_y_vs__relig_002
fc_y_vs__relig_003
fc_y_vs__relig_004
fc_y_vs__relig_005
fc_y_vs__relig_006
fc_y_vs__relig_007
Excluded values:
777
compute_fc_y_vs__relig_nm( data, name = "fc_y_vs__relig_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__relig_nm( data, name = "fc_y_vs__relig_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__supp_nm
(Values Scale [Youth] (Family support): Number
missing)
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
Excluded values:
777
compute_fc_y_vs__supp_nm( data, name = "fc_y_vs__supp_nm", exclude = c("777"), combine = TRUE )compute_fc_y_vs__supp_nm( data, name = "fc_y_vs__supp_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_vs_all(data)compute_fc_y_vs_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_vs_all(data) ## End(Not run)## Not run: compute_fc_y_vs_all(data) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_fc_y_wpss_all(data)compute_fc_y_wpss_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_fc_y_wpss_all(data) ## End(Not run)## Not run: compute_fc_y_wpss_all(data) ## End(Not run)
Computes the summary score fc_y_wpss_nm
(Wills Problem Solving Scale [Youth]: Number missing)
Summarized variables:
fc_y_wpss_001
fc_y_wpss_002
fc_y_wpss_003
fc_y_wpss_004
fc_y_wpss_005
fc_y_wpss_006
Excluded values: none
compute_fc_y_wpss_nm(data, name = "fc_y_wpss_nm", combine = TRUE)compute_fc_y_wpss_nm(data, name = "fc_y_wpss_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Pipeline wrapper that processes Fitbit minute-level activity data into a daily summary table. Applies heart rate-based exclusions and recovery identification, then aggregates minute totals, exclusion summaries, step counts, intensity scores, and sleep presence into a single day-level data frame. Optionally appends Fitbit-generated daily QC measures.
compute_fitbit_activity_table( data_activity, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = 1440, append_daily_fitbit_qc, qc_threshold = 0.8, offset = "12:00", min_actv_minutes )compute_fitbit_activity_table( data_activity, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = 1440, append_daily_fitbit_qc, qc_threshold = 0.8, offset = "12:00", min_actv_minutes )
data_activity |
tbl. Data frame with |
data_daily |
tbl. Daily-level Fitbit-generated summary data containing
|
hr_low |
numeric. Lower bound threshold for valid heart rate values. |
hr_high |
numeric or NULL. Optional upper bound threshold for valid heart rate values. If NULL, no upper threshold is applied. |
hr_rep_day |
numeric. Threshold (number of epochs) for identifying repeated heart rate values during wake/activity periods. |
hr_rep_sleep |
numeric. Threshold (number of epochs) for identifying repeated heart rate values during sleep periods. |
bin_minutes |
numeric. Number of minutes used to bin activity data when computing intensity scores (e.g., 1440 for daily aggregation). |
append_daily_fitbit_qc |
logical. If TRUE, add Fitbit-provided step count and QC measures. |
qc_threshold |
numeric, between 0 and 1. Minimum percentage of Fitbit step count that must be met by computed active step count for QC to pass (Default: 0.8). |
offset |
character. Time of day (HH:MM) cutoff. |
min_actv_minutes |
numeric. Minimum number of active minutes required
for a day to pass quality control. Used to create a |
tbl. A daily-level summarized data frame with the following components:
Identifiers and time variables:
participant_id, session_id
wk: Study week index
day: Study day index
dt: Calendar date
dt_day: Day of week (labeled)
dt_wknd: Indicator for weekend days
Activity and sleep measures:
min_total: Total valid minutes
min_actv: Active (non-sleep) minutes
min_slp: Sleep minutes
min_nap_slp: Nap sleep minutes
Step count measures:
steps_total: Total steps after exclusions
steps_actv: Steps during active minutes after exclusions
steps: Total steps before exclusions
steps_fitb: Fitbit-reported daily steps
Energy expenditure and intensity-based activity measures:
mets: Mean METs
mets_actv: Mean METs during active minutes
min_intnst_*: Minutes spent in sedentary, light, moderate, and
vigorous activity (total and active-only variants)
Heart rate exclusion summaries:
excl_min_*: Minutes excluded due to heart rate criteria (low, high,
missing, repeated) for both activity and sleep domains
Heart rate and QC metrics:
hrate_rest_fitb: Resting heart rate (Fitbit daily summary)
qc_600min: Indicator for >= 600 valid active minutes
qc_steps: Indicator for valid step counts based on Fitbit comparison
pcnt_steps_fitb: Proportion of calculated steps relative to
Fitbit-reported steps
Flags:
flg_30sec: Indicator that valid 30-second sleep data exists for the day
flg_any: Indicator that any valid data exists for the day
Computes all daily activity scores (extended).
compute_fitbit_activity_table_ext( data_activity, data_daily = NULL, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = 1440, append_daily_fitbit_qc = TRUE, qc_threshold = 0.8, offset = "12:00", min_actv_minutes, main_duration, gap = 90 )compute_fitbit_activity_table_ext( data_activity, data_daily = NULL, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = 1440, append_daily_fitbit_qc = TRUE, qc_threshold = 0.8, offset = "12:00", min_actv_minutes, main_duration, gap = 90 )
data_activity |
tbl. Data frame with activity data. |
data_daily |
tbl. Data frame with daily Fitbit summary data. |
hr_low |
numeric. Lower bound threshold for valid heart rate values. |
hr_high |
numeric or NULL. Optional upper bound threshold. |
hr_rep_day |
numeric. Threshold for identifying repeated HR. |
hr_rep_sleep |
numeric. Threshold for identifying repeated HR. |
bin_minutes |
numeric. Number of minutes used to bin data. |
append_daily_fitbit_qc |
logical. If TRUE, add Fitbit-provided steps. |
qc_threshold |
numeric, between 0 and 1. Minimum percentage of Fitbit step count that must be met by computed active step count for QC to pass. |
offset |
character. Time of day (HH:MM) cutoff. |
min_actv_minutes |
numeric. Minimum number of active minutes required
for a day to pass quality control. Used to create a |
main_duration |
numeric. Minimum duration in minutes. |
gap |
numeric. Maximum allowed gap. |
tbl. A daily-level extended activity summary.
data_activity: fitbit_raw_activity or fitbit_covid_raw_activity
data_daily: fitbit_raw_metrics or fitbit_covid_raw_metrics
compute_fitbit_activity_table()
Generates weekly activity summaries from daily Fitbit activity data.
This wrapper function applies a standardized weekly aggregation pipeline
using compute_fitbit_weekly_summary() and the summarize_activity()
function to compute weekly activity metrics at the participant-session level.
Only days passing minimum quality control thresholds (qc_600min and
qc_steps) are included in the weekly aggregation.
compute_fitbit_activity_week(df, filter_expr = qc_600min & qc_steps)compute_fitbit_activity_week(df, filter_expr = qc_600min & qc_steps)
df |
tbl. Daily-level Fitbit activity dataset (standard or extended),
typically |
filter_expr |
expression. Logical filtering condition applied to the input dataset before summarization (e.g., QC thresholds). which retains only days with at least 600 valid minutes and passing step count quality checks. |
This function standardizes weekly activity computation across datasets by enforcing consistent filtering, aggregation, and output structure.
tbl. Weekly activity dataset containing:
Week identifiers (wk, wk_type)
Day counts (n_day, n_wkdy, n_wknd)
Activity summary metrics (steps, METs, intensity minutes, heart rate)
Weekly quality control flag (qc_wk)
df: fitbit_ss_activity_day or fitbit_ss_ext_activity_day
(daily Fitbit activity dataset with QC flags)
Processes Fitbit minute-level data to generate daily sleep summary scores. This function integrates multiple processing steps, including heart rate-based exclusions and calculation of sleep measures, aggregated at the day level.
compute_fitbit_sleep_table( data_activity, data_sleep_combined, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = NULL, offset = "12:00", min_slp_minutes = 300 )compute_fitbit_sleep_table( data_activity, data_sleep_combined, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = NULL, offset = "12:00", min_slp_minutes = 300 )
data_activity |
tbl. Data frame with the following columns with minute-level epoch data with the following columns:
|
data_sleep_combined |
tbl. Data frame with the following columns in 30-second epoch level with the following columns:
|
data_daily |
tbl. Daily-level Fitbit-generated summary data containing:
|
hr_low |
numeric. Lower bound threshold for valid heart rate values. |
hr_high |
numeric or NULL. Optional upper bound threshold for valid heart rate values. If NULL, no upper threshold is applied. |
hr_rep_day |
numeric. Threshold (number of epochs) for identifying repeated heart rate values during wake/activity periods. |
hr_rep_sleep |
numeric. Threshold (number of epochs) for identifying repeated heart rate values during sleep periods. |
bin_minutes |
numeric. Number of minutes used to bin activity data when
computing intensity scores (e.g., 1440 for daily aggregation). Default is
NULL. When NULL, it uses |
offset |
character. Time of day (HH:MM) used as the cutoff for defining the sleep day. Timestamps occuring after this time are assigned to the next day. |
min_slp_minutes |
numeric. Minimum number of sleep minutes required
for a day to pass quality control. Used to create a |
tbl. A daily-level summarized data frame with the following components:
Identifiers and time variables:
participant_id, session_id
wk: Study week index
day: Study day index
dt: Calendar date
dt_day: Day of week (labeled)
dt_wknd: Indicator for weekend days
Sleep timing measures:
dtt_start_bed, dtt_end_bed: Bed interval start and end times
dtt_start_slp, dtt_end_slp: Sleep interval start and end times
Sleep duration measures:
min_total_slp: Total sleep duration
min_asleep_slp, min_restless_slp, min_light_slp,
min_deep_slp, min_rem_slp: Stage-specific sleep durations
min_nap_slp: Nap sleep duration
min_wake: Wake minutes during sleep intervals
min_waso: Wake after sleep onset (WASO)
n_waso: Number of WASO episodes
Heart rate summaries by sleep stage:
hrate_awake_slp, hrate_restless_slp, hrate_asleep_slp
hrate_light_slp, hrate_deep_slp, hrate_rem_slp
hrate_nap_slp: Mean heart rate during nap sleep
hrate_rest_fitb: Daily resting heart rate from Fitbit
Heart rate exclusion measures:
excl_min_total_slp: Total excluded sleep minutes
excl_min_lowhrate_slp: Minutes excluded due to low heart rate
excl_min_nohrate_slp: Minutes excluded due to missing heart rate
excl_min_highhrate_slp: Minutes excluded due to high heart rate
excl_min_repeathrate_slp: Minutes excluded due to repeated heart rate
min_extra_nohrate_slp: Additional plausible sleep minutes excluded
Quality control and flags:
qc_300min: Indicator for >= 300 minutes of valid sleep
flg_slp: Indicator for implausible sleep structure
flg_any: Indicator that any sleep data are present
flg_slp, sleep timing and WASO variables are only calculated when
bin_minutes is NULL. Calculations depend on offset dates and cannot operate
on binned intervals. Returns an empty columns otherwise.
data_activity: fitbit_raw_activity or fitbit_covid_raw_activity
data_sleep_combined: fitbit_raw_sleep or fitbit_covid_raw_sleep
data_daily: fitbit_raw_metrics or fitbit_covid_raw_metrics
This function extends the standard sleep pipeline by grouping 30-second sleep epochs into continuous sleep blocks based on a configurable gap threshold, and redefining main sleep periods based on block duration. Heart rate exclusion logic is applied both prior to and after block construction to ensure consistency across raw and reconstructed sleep structures.
compute_fitbit_sleep_table_ext( data_activity, data_sleep_combined, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = NULL, offset = "12:00", min_slp_minutes, main_duration = 180, gap = 90 )compute_fitbit_sleep_table_ext( data_activity, data_sleep_combined, data_daily, hr_low = 50, hr_high = NULL, hr_rep_day = 10, hr_rep_sleep = 30, bin_minutes = NULL, offset = "12:00", min_slp_minutes, main_duration = 180, gap = 90 )
data_activity |
tbl. Epoch-level activity data used to derive heart rate exclusion flags. |
data_sleep_combined |
tbl. 30-second sleep epoch data containing sleep stage and timestamp information. |
data_daily |
tbl. Daily Fitbit summary data including resting heart rate. |
hr_low |
numeric. Lower threshold for valid heart rate values. |
hr_high |
numeric or NULL. Optional upper threshold for valid heart rate values. |
hr_rep_day |
numeric. Threshold (number of epochs) for repeated heart rate detection in daytime activity. |
hr_rep_sleep |
numeric. Threshold (number of epochs) for repeated heart rate detection in sleep. |
bin_minutes |
numeric. Number of minutes used to bin data. |
offset |
character. Time-of-day cutoff used to define sleep-day boundaries. |
min_slp_minutes |
numeric. Minimum number of sleep minutes required
for a day to pass quality control. Used to create a |
main_duration |
numeric. Minumum duration in minutes for a sleep episode to be qualify as a main sleep episode. |
gap |
numeric. Maximum allowed gap (in minutes) between consecutive sleep epochs before a new sleep episode is defined. |
This extended pipeline differs from the standard sleep table by introducing a episode-based reconstruction step. Sleep epochs are grouped into continuous episodes using a configurable gap threshold, and episode duration is used to define main sleep.
tbl. A daily-level extended sleep summary table containing:
Identifiers and time variables:
participant_id, session_id
wk: Study week index
day: Study day index
dt: Sleep-aligned date
dt_day: Day of week
dt_wknd: Weekend indicator
Sleep timing and block structure:
dtt_start_bed, dtt_end_bed
dtt_start_slp, dtt_end_slp
Sleep duration metrics:
min_total_slp, min_asleep_slp, min_restless_slp,
min_light_slp, min_deep_slp, min_rem_slp, min_nap_slp
min_waso, min_wake, n_waso
Heart rate summaries by sleep stage:
hrate_awake_slp, hrate_restless_slp, hrate_asleep_slp
hrate_light_slp, hrate_deep_slp, hrate_rem_slp
hrate_nap_slp, hrate_rest_fitb
Heart rate exclusion metrics:
excl_min_total_slp, excl_min_lowhrate_slp
excl_min_nohrate_slp, excl_min_highhrate_slp
excl_min_repeathrate_slp, min_extra_nohrate_slp
Quality control flags:
qc_300min: Indicator for >= 300 minutes of sleep
flg_slp: Flag for implausible sleep structure
flg_any: Indicator for any valid sleep data
data_activity: fitbit_raw_activity or fitbit_covid_raw_activity
data_sleep_combined: fitbit_raw_sleep or fitbit_covid_raw_sleep
data_daily: fitbit_raw_metrics or fitbit_covid_raw_metrics
This wrapper function applies a standardized weekly aggregation pipeline
using compute_fitbit_weekly_summary() and the summarize_sleep() function
to compute weekly sleep metrics at the participant-session level.
Only days passing minimum quality control thresholds (qc_300min) are
included in the weekly aggregation.
compute_fitbit_sleep_week(df, filter_expr = qc_300min)compute_fitbit_sleep_week(df, filter_expr = qc_300min)
df |
tbl. Daily-level Fitbit sleep dataset (standard or extended),
typically |
filter_expr |
expression. Logical filtering condition applied to the input dataset before summarization (e.g., QC thresholds). |
This function ensures consistent weekly aggregation of sleep metrics across standard and extended Fitbit datasets. It inherits QC filtering from the parent pipeline and preserves both total and stage-specific sleep summaries.
tbl. Weekly sleep dataset containing:
Week identifiers (wk, wk_type)
Day counts (n_day, n_wkdy, n_wknd)
Sleep timing metrics (bed/sleep onset and offset)
Sleep duration and stage summaries
Heart rate–derived sleep metrics
Wake-after-sleep-onset metrics
Weekly quality control flag (qc_wk)
df: fitbit_ss_sleep_day or fitbit_ss_ext_sleep_day
(daily Fitbit sleep dataset with QC flags)
Generates weekly summary tables using a user-supplied summarization function, with stratification by weekday, weekend, and full-week estimates.
This function standardizes weekly aggregation by: (1) filtering valid records, (2) computing day counts for quality control, (3) applying a user-defined summarization function, and (4) producing three parallel weekly summaries (whole week, weekday-only, and weekend-only).
compute_fitbit_weekly_summary( df, wkdy_min = 3, wknd_min = 1, summarize_fn, filter_expr )compute_fitbit_weekly_summary( df, wkdy_min = 3, wknd_min = 1, summarize_fn, filter_expr )
df |
tbl. Input daily-level dataset containing at minimum:
|
wkdy_min |
numeric. Minimum number of weekday observations required for a valid weekly weekday estimate. |
wknd_min |
numeric. Minimum number of weekend observations required for a valid weekly weekend estimate. |
summarize_fn |
function. A user-defined function that takes a filtered
dataset and returns weekly summaries grouped by
|
filter_expr |
expression. Logical filtering condition applied to the input dataset before summarization (e.g., QC thresholds). |
The function uses stratified counting to ensure that weekly estimates are interpretable in the context of data completeness. The QC rule differs by strata:
Whole week: requires both weekday and weekend minimum counts
Weekday/weekend: require minimum counts within their respective subsets
The summarize_fn argument allows flexible reuse across sleep and activity
pipelines while maintaining consistent weekly structure.
tbl. A combined weekly dataset containing three types of summaries:
wk_type = 2: Whole-week estimates (weekday + weekend combined)
wk_type = 1: Weekend-only estimates
wk_type = 0: Weekday-only estimates
Each row includes:
Weekly summary metrics from summarize_fn
Day count variables (n_day, n_wkdy, n_wknd)
Quality control flag qc_wk indicating sufficient coverage
Computes the summary score mh_p_abcl__afs__frnd_sum
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): Sum
Summarized variables:
mh_p_abcl__frnd_001
mh_p_abcl__frnd_002
mh_p_abcl__frnd_003
mh_p_abcl__frnd_004
Excluded values:
777
999
Validation criterion: maximally 0 of 4 items missing
compute_mh_p_abcl__afs__frnd_sum( data, name = "mh_p_abcl__afs__frnd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__afs__frnd_sum( data, name = "mh_p_abcl__afs__frnd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__afs__frnd_nm()
## Not run: compute_mh_p_abcl__afs__frnd_sum(data) |> select( any_of(c("mh_p_abcl__afs__frnd_sum", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__afs__frnd_sum(data) |> select( any_of(c("mh_p_abcl__afs__frnd_sum", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__afs__frnd_tscore
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): T-score
Summarized variables:
mh_p_abcl__frnd_001
mh_p_abcl__frnd_002
mh_p_abcl__frnd_003
mh_p_abcl__frnd_004
Excluded values:
777
999
Validation criterion: maximally 0 of 4 items missing
compute_mh_p_abcl__afs__frnd_tscore( data, data_norm = NULL, name = "mh_p_abcl__afs__frnd_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__afs__frnd_tscore( data, data_norm = NULL, name = "mh_p_abcl__afs__frnd_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__afs__frnd_nm()
## Not run: compute_mh_p_abcl__afs__frnd_tscore(data) |> select( any_of(c("mh_p_abcl__afs__frnd_tscore", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__afs__frnd_tscore(data) |> select( any_of(c("mh_p_abcl__afs__frnd_tscore", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__critic_sum
Adult Behavior Checklist [Parent] (Critical items): Sum
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 1 of 19 items missing
compute_mh_p_abcl__critic_sum( data, name = "mh_p_abcl__critic_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__critic_sum( data, name = "mh_p_abcl__critic_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__critic_nm()
## Not run: compute_mh_p_abcl__critic_sum(data) |> select( any_of(c("mh_p_abcl__critic_sum", vars_mh_p_abcl__critic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__critic_sum(data) |> select( any_of(c("mh_p_abcl__critic_sum", vars_mh_p_abcl__critic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__critic_tscore
Adult Behavior Checklist [Parent] (Critical items): T-score
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 1 of 19 items missing
compute_mh_p_abcl__critic_tscore( data, data_norm = NULL, name = "mh_p_abcl__critic_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__critic_tscore( data, data_norm = NULL, name = "mh_p_abcl__critic_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__critic_nm()
## Not run: compute_mh_p_abcl__critic_tscore(data) |> select( any_of(c("mh_p_abcl__critic_tscore", vars_mh_p_abcl__critic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__critic_tscore(data) |> select( any_of(c("mh_p_abcl__critic_tscore", vars_mh_p_abcl__critic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__adhd_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum
Summarized variables:
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_001
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_abcl__dsm__adhd_sum( data, name = "mh_p_abcl__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__adhd_sum( data, name = "mh_p_abcl__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__adhd_nm()
## Not run: compute_mh_p_abcl__dsm__adhd_sum(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_sum", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__adhd_sum(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_sum", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__adhd_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
T-score
Summarized variables:
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_001
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_abcl__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__adhd_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__adhd_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__adhd_nm()
## Not run: compute_mh_p_abcl__dsm__adhd_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_tscore", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__adhd_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_tscore", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__antsoc_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Sum
Summarized variables:
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 1 of 20 items missing
compute_mh_p_abcl__dsm__antsoc_sum( data, name = "mh_p_abcl__dsm__antsoc_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__antsoc_sum( data, name = "mh_p_abcl__dsm__antsoc_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__antsoc_nm()
## Not run: compute_mh_p_abcl__dsm__antsoc_sum(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_sum", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__antsoc_sum(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_sum", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__antsoc_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): T-score
Summarized variables:
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 1 of 20 items missing
compute_mh_p_abcl__dsm__antsoc_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__antsoc_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__antsoc_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__antsoc_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__antsoc_nm()
## Not run: compute_mh_p_abcl__dsm__antsoc_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_tscore", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__antsoc_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_tscore", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__anx_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): Sum
Summarized variables:
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_abcl__dsm__anx_sum( data, name = "mh_p_abcl__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__anx_sum( data, name = "mh_p_abcl__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__anx_nm()
## Not run: compute_mh_p_abcl__dsm__anx_sum(data) |> select( any_of(c("mh_p_abcl__dsm__anx_sum", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__anx_sum(data) |> select( any_of(c("mh_p_abcl__dsm__anx_sum", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__anx_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): T-score
Summarized variables:
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_abcl__dsm__anx_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__anx_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__anx_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__anx_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__anx_nm()
## Not run: compute_mh_p_abcl__dsm__anx_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__anx_tscore", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__anx_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__anx_tscore", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__avoid_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Sum
Summarized variables:
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_abcl__dsm__avoid_sum( data, name = "mh_p_abcl__dsm__avoid_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__avoid_sum( data, name = "mh_p_abcl__dsm__avoid_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__avoid_nm()
## Not run: compute_mh_p_abcl__dsm__avoid_sum(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_sum", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__avoid_sum(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_sum", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__avoid_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): T-score
Summarized variables:
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_abcl__dsm__avoid_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__avoid_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__avoid_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__avoid_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__avoid_nm()
## Not run: compute_mh_p_abcl__dsm__avoid_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_tscore", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__avoid_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_tscore", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__dep_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Sum
Summarized variables:
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_abcl__dsm__dep_sum( data, name = "mh_p_abcl__dsm__dep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__dep_sum( data, name = "mh_p_abcl__dsm__dep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__dep_nm()
## Not run: compute_mh_p_abcl__dsm__dep_sum(data) |> select( any_of(c("mh_p_abcl__dsm__dep_sum", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__dep_sum(data) |> select( any_of(c("mh_p_abcl__dsm__dep_sum", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__dep_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): T-score
Summarized variables:
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_abcl__dsm__dep_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__dep_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__dep_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__dep_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__dep_nm()
## Not run: compute_mh_p_abcl__dsm__dep_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__dep_tscore", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__dep_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__dep_tscore", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__somat_sum
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
Summarized variables:
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_abcl__dsm__somat_sum( data, name = "mh_p_abcl__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__somat_sum( data, name = "mh_p_abcl__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__somat_nm()
## Not run: compute_mh_p_abcl__dsm__somat_sum(data) |> select( any_of(c("mh_p_abcl__dsm__somat_sum", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__somat_sum(data) |> select( any_of(c("mh_p_abcl__dsm__somat_sum", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__somat_tscore
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): T-score
Summarized variables:
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_abcl__dsm__somat_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__somat_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__dsm__somat_tscore( data, data_norm = NULL, name = "mh_p_abcl__dsm__somat_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__dsm__somat_nm()
## Not run: compute_mh_p_abcl__dsm__somat_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__somat_tscore", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__somat_tscore(data) |> select( any_of(c("mh_p_abcl__dsm__somat_tscore", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drg_sum
Adult Behavior Checklist [Parent] (Days drug use): Sum
Summarized variables:
mh_p_abcl__drg_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__drg_sum( data, name = "mh_p_abcl__su__drg_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__drg_sum( data, name = "mh_p_abcl__su__drg_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__drg_nm()
## Not run: compute_mh_p_abcl__su__drg_sum(data) |> select( any_of(c("mh_p_abcl__su__drg_sum", vars_mh_p_abcl__su__drg)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drg_sum(data) |> select( any_of(c("mh_p_abcl__su__drg_sum", vars_mh_p_abcl__su__drg)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drg_tscore
Adult Behavior Checklist [Parent] (Days drug use): T-score
Summarized variables:
mh_p_abcl__drg_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__drg_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__drg_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__drg_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__drg_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__drg_nm()
## Not run: compute_mh_p_abcl__su__drg_tscore(data) |> select( any_of(c("mh_p_abcl__su__drg_tscore", vars_mh_p_abcl__su__drg)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drg_tscore(data) |> select( any_of(c("mh_p_abcl__su__drg_tscore", vars_mh_p_abcl__su__drg)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drunk_sum
Adult Behavior Checklist [Parent] (Days Drunk): Sum
Summarized variables:
mh_p_abcl__drunk_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__drunk_sum( data, name = "mh_p_abcl__su__drunk_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__drunk_sum( data, name = "mh_p_abcl__su__drunk_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__drunk_nm()
## Not run: compute_mh_p_abcl__su__drunk_sum(data) |> select( any_of(c("mh_p_abcl__su__drunk_sum", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drunk_sum(data) |> select( any_of(c("mh_p_abcl__su__drunk_sum", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drunk_tscore
Adult Behavior Checklist [Parent] (Days Drunk): T-score
Summarized variables:
mh_p_abcl__drunk_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__drunk_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__drunk_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__drunk_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__drunk_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__drunk_nm()
## Not run: compute_mh_p_abcl__su__drunk_tscore(data) |> select( any_of(c("mh_p_abcl__su__drunk_tscore", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drunk_tscore(data) |> select( any_of(c("mh_p_abcl__su__drunk_tscore", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__nic_sum
Adult Behavior Checklist [Parent] (Tobacco per day): Sum
Summarized variables:
mh_p_abcl__nic_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__nic_sum( data, name = "mh_p_abcl__su__nic_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__nic_sum( data, name = "mh_p_abcl__su__nic_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__nic_nm()
## Not run: compute_mh_p_abcl__su__nic_sum(data) |> select( any_of(c("mh_p_abcl__su__nic_sum", vars_mh_p_abcl__su__nic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__nic_sum(data) |> select( any_of(c("mh_p_abcl__su__nic_sum", vars_mh_p_abcl__su__nic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__nic_tscore
Adult Behavior Checklist [Parent] (Tobacco per day): T-score
Summarized variables:
mh_p_abcl__nic_001
Excluded values:
777
999
Validation criterion: maximally 0 of 1 items missing
compute_mh_p_abcl__su__nic_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__nic_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su__nic_tscore( data, data_norm = NULL, name = "mh_p_abcl__su__nic_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__su__nic_nm()
## Not run: compute_mh_p_abcl__su__nic_tscore(data) |> select( any_of(c("mh_p_abcl__su__nic_tscore", vars_mh_p_abcl__su__nic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__nic_tscore(data) |> select( any_of(c("mh_p_abcl__su__nic_tscore", vars_mh_p_abcl__su__nic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su_sum
Adult Behavior Checklist [Parent] (Substance use): Sum
Summarized variables:
mh_p_abcl__drg_001
mh_p_abcl__drunk_001
mh_p_abcl__nic_001
Excluded values:
777
999
Validation criterion: maximally 0 of 3 items missing
compute_mh_p_abcl__su_sum( data, name = "mh_p_abcl__su_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su_sum( data, name = "mh_p_abcl__su_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_abcl__su_sum(data) |> select( any_of(c("mh_p_abcl__su_sum", vars_mh_p_abcl__su)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su_sum(data) |> select( any_of(c("mh_p_abcl__su_sum", vars_mh_p_abcl__su)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su_tscore
Adult Behavior Checklist [Parent] (Substance use): T-score
Summarized variables:
mh_p_abcl__drg_001
mh_p_abcl__drunk_001
mh_p_abcl__nic_001
Excluded values:
777
999
Validation criterion: maximally 0 of 3 items missing
compute_mh_p_abcl__su_tscore( data, data_norm = NULL, name = "mh_p_abcl__su_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__su_tscore( data, data_norm = NULL, name = "mh_p_abcl__su_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_abcl__su_tscore(data) |> select( any_of(c("mh_p_abcl__su_tscore", vars_mh_p_abcl__su)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su_tscore(data) |> select( any_of(c("mh_p_abcl__su_tscore", vars_mh_p_abcl__su)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__aggr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Sum
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
Excluded values:
777
999
Validation criterion: maximally 1 of 16 items missing
compute_mh_p_abcl__synd__aggr_sum( data, name = "mh_p_abcl__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__aggr_sum( data, name = "mh_p_abcl__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__aggr_nm()
## Not run: compute_mh_p_abcl__synd__aggr_sum(data) |> select( any_of(c("mh_p_abcl__synd__aggr_sum", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__aggr_sum(data) |> select( any_of(c("mh_p_abcl__synd__aggr_sum", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__aggr_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): T-score
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
Excluded values:
777
999
Validation criterion: maximally 1 of 16 items missing
compute_mh_p_abcl__synd__aggr_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__aggr_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__aggr_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__aggr_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__aggr_nm()
## Not run: compute_mh_p_abcl__synd__aggr_tscore(data) |> select( any_of(c("mh_p_abcl__synd__aggr_tscore", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__aggr_tscore(data) |> select( any_of(c("mh_p_abcl__synd__aggr_tscore", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__anxdep_sum
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Sum
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_abcl__synd__anxdep_sum( data, name = "mh_p_abcl__synd__anxdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__anxdep_sum( data, name = "mh_p_abcl__synd__anxdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__anxdep_nm()
## Not run: compute_mh_p_abcl__synd__anxdep_sum(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_sum", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__anxdep_sum(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_sum", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__anxdep_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): T-score
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_abcl__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__anxdep_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__anxdep_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__anxdep_nm()
## Not run: compute_mh_p_abcl__synd__anxdep_tscore(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_tscore", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__anxdep_tscore(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_tscore", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__attn_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Sum
Summarized variables:
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_abcl__synd__attn_sum( data, name = "mh_p_abcl__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__attn_sum( data, name = "mh_p_abcl__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__attn_nm()
## Not run: compute_mh_p_abcl__synd__attn_sum(data) |> select( any_of(c("mh_p_abcl__synd__attn_sum", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__attn_sum(data) |> select( any_of(c("mh_p_abcl__synd__attn_sum", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__attn_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): T-score
Summarized variables:
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_abcl__synd__attn_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__attn_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__attn_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__attn_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__attn_nm()
## Not run: compute_mh_p_abcl__synd__attn_tscore(data) |> select( any_of(c("mh_p_abcl__synd__attn_tscore", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__attn_tscore(data) |> select( any_of(c("mh_p_abcl__synd__attn_tscore", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__ext_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - External): Sum
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
Validation criterion: maximally 2 of 35 items missing
compute_mh_p_abcl__synd__ext_sum( data, name = "mh_p_abcl__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__ext_sum( data, name = "mh_p_abcl__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__ext_nm()
## Not run: compute_mh_p_abcl__synd__ext_sum(data) |> select( any_of(c("mh_p_abcl__synd__ext_sum", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__ext_sum(data) |> select( any_of(c("mh_p_abcl__synd__ext_sum", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__ext_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - External): T-score
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
Validation criterion: maximally 2 of 35 items missing
compute_mh_p_abcl__synd__ext_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__ext_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__ext_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__ext_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__ext_nm()
## Not run: compute_mh_p_abcl__synd__ext_tscore(data) |> select( any_of(c("mh_p_abcl__synd__ext_tscore", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__ext_tscore(data) |> select( any_of(c("mh_p_abcl__synd__ext_tscore", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__int_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Sum
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 32 items missing
compute_mh_p_abcl__synd__int_sum( data, name = "mh_p_abcl__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__int_sum( data, name = "mh_p_abcl__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__int_nm()
## Not run: compute_mh_p_abcl__synd__int_sum(data) |> select( any_of(c("mh_p_abcl__synd__int_sum", vars_mh_p_abcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__int_sum(data) |> select( any_of(c("mh_p_abcl__synd__int_sum", vars_mh_p_abcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__int_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
T-score
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 32 items missing
compute_mh_p_abcl__synd__int_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__int_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__int_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__int_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__int_nm()
## Not run: compute_mh_p_abcl__synd__int_tscore(data) |> select( any_of(c("mh_p_abcl__synd__int_tscore", vars_mh_p_abcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__int_tscore(data) |> select( any_of(c("mh_p_abcl__synd__int_tscore", vars_mh_p_abcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__intru_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Sum
Summarized variables:
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_abcl__synd__intru_sum( data, name = "mh_p_abcl__synd__intru_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__intru_sum( data, name = "mh_p_abcl__synd__intru_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__intru_nm()
## Not run: compute_mh_p_abcl__synd__intru_sum(data) |> select( any_of(c("mh_p_abcl__synd__intru_sum", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__intru_sum(data) |> select( any_of(c("mh_p_abcl__synd__intru_sum", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__intru_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive):
T-score
Summarized variables:
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_abcl__synd__intru_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__intru_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__intru_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__intru_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__intru_nm()
## Not run: compute_mh_p_abcl__synd__intru_tscore(data) |> select( any_of(c("mh_p_abcl__synd__intru_tscore", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__intru_tscore(data) |> select( any_of(c("mh_p_abcl__synd__intru_tscore", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__othpr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Sum
Summarized variables:
mh_p_abcl__othpr_001
mh_p_abcl__othpr_002
mh_p_abcl__othpr_003
mh_p_abcl__othpr_004
mh_p_abcl__othpr_005
mh_p_abcl__othpr_006
mh_p_abcl__othpr_007
mh_p_abcl__othpr_008
mh_p_abcl__othpr_009
mh_p_abcl__othpr_010
mh_p_abcl__othpr_011
mh_p_abcl__othpr_012
mh_p_abcl__othpr__adhd_001
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
mh_p_abcl__othpr__avoid_001
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
Excluded values:
777
999
Validation criterion: maximally 1 of 25 items missing
compute_mh_p_abcl__synd__othpr_sum( data, name = "mh_p_abcl__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__othpr_sum( data, name = "mh_p_abcl__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__othpr_nm()
## Not run: compute_mh_p_abcl__synd__othpr_sum(data) |> select( any_of(c("mh_p_abcl__synd__othpr_sum", vars_mh_p_abcl__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__othpr_sum(data) |> select( any_of(c("mh_p_abcl__synd__othpr_sum", vars_mh_p_abcl__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__rule_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Sum
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_abcl__synd__rule_sum( data, name = "mh_p_abcl__synd__rule_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__rule_sum( data, name = "mh_p_abcl__synd__rule_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__rule_nm()
## Not run: compute_mh_p_abcl__synd__rule_sum(data) |> select( any_of(c("mh_p_abcl__synd__rule_sum", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__rule_sum(data) |> select( any_of(c("mh_p_abcl__synd__rule_sum", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__rule_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): T-score
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_abcl__synd__rule_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__rule_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__rule_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__rule_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__rule_nm()
## Not run: compute_mh_p_abcl__synd__rule_tscore(data) |> select( any_of(c("mh_p_abcl__synd__rule_tscore", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__rule_tscore(data) |> select( any_of(c("mh_p_abcl__synd__rule_tscore", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__som_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Sum
Summarized variables:
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__som_sum( data, name = "mh_p_abcl__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__som_sum( data, name = "mh_p_abcl__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__som_nm()
## Not run: compute_mh_p_abcl__synd__som_sum(data) |> select( any_of(c("mh_p_abcl__synd__som_sum", vars_mh_p_abcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__som_sum(data) |> select( any_of(c("mh_p_abcl__synd__som_sum", vars_mh_p_abcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__som_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): T-score
Summarized variables:
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__som_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__som_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__som_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__som_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__som_nm()
## Not run: compute_mh_p_abcl__synd__som_tscore(data) |> select( any_of(c("mh_p_abcl__synd__som_tscore", vars_mh_p_abcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__som_tscore(data) |> select( any_of(c("mh_p_abcl__synd__som_tscore", vars_mh_p_abcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__tho_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Sum
Summarized variables:
mh_p_abcl__tho_001
mh_p_abcl__tho_002
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_005
mh_p_abcl__tho_006
mh_p_abcl__tho_007
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__tho_sum( data, name = "mh_p_abcl__synd__tho_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__tho_sum( data, name = "mh_p_abcl__synd__tho_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__tho_nm()
## Not run: compute_mh_p_abcl__synd__tho_sum(data) |> select( any_of(c("mh_p_abcl__synd__tho_sum", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__tho_sum(data) |> select( any_of(c("mh_p_abcl__synd__tho_sum", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__tho_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
T-score
Summarized variables:
mh_p_abcl__tho_001
mh_p_abcl__tho_002
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_005
mh_p_abcl__tho_006
mh_p_abcl__tho_007
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__tho_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__tho_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__tho_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__tho_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__tho_nm()
## Not run: compute_mh_p_abcl__synd__tho_tscore(data) |> select( any_of(c("mh_p_abcl__synd__tho_tscore", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__tho_tscore(data) |> select( any_of(c("mh_p_abcl__synd__tho_tscore", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__wthdr_sum
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Sum
Summarized variables:
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__wthdr_sum( data, name = "mh_p_abcl__synd__wthdr_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__wthdr_sum( data, name = "mh_p_abcl__synd__wthdr_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__wthdr_nm()
## Not run: compute_mh_p_abcl__synd__wthdr_sum(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_sum", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__wthdr_sum(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_sum", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__wthdr_tscore
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn):
T-score
Summarized variables:
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_abcl__synd__wthdr_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__wthdr_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl__synd__wthdr_tscore( data, data_norm = NULL, name = "mh_p_abcl__synd__wthdr_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_abcl__synd__wthdr_nm()
## Not run: compute_mh_p_abcl__synd__wthdr_tscore(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_tscore", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__wthdr_tscore(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_tscore", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)
This function computes all summary scores for the mh_p_abcl form. Make sure to have all necessary columns in the data frame.
compute_mh_p_abcl_all(data)compute_mh_p_abcl_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_abcl_all(data) ## End(Not run)## Not run: compute_mh_p_abcl_all(data) ## End(Not run)
Computes the summary score mh_p_abcl_sum
Adult Behavior Checklist [Parent]: Sum
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__rule_003
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__som_001
mh_p_abcl__othpr_001
mh_p_abcl__othpr_002
mh_p_abcl__othpr_003
mh_p_abcl__othpr_004
mh_p_abcl__othpr_005
mh_p_abcl__othpr_006
mh_p_abcl__othpr_007
mh_p_abcl__othpr_008
mh_p_abcl__othpr_009
mh_p_abcl__othpr_010
mh_p_abcl__othpr_011
mh_p_abcl__othpr_012
mh_p_abcl__tho_005
mh_p_abcl__tho_007
Excluded values:
777
999
Validation criterion: maximally 8 of 118 items missing
compute_mh_p_abcl_sum( data, name = "mh_p_abcl_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl_sum( data, name = "mh_p_abcl_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_abcl_sum(data) |> select( any_of(c("mh_p_abcl_sum", vars_mh_p_abcl)) ) ## End(Not run)## Not run: compute_mh_p_abcl_sum(data) |> select( any_of(c("mh_p_abcl_sum", vars_mh_p_abcl)) ) ## End(Not run)
Computes the summary score mh_p_abcl_tscore
Adult Behavior Checklist [Parent]: T-score
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__rule_003
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__som_001
mh_p_abcl__othpr_001
mh_p_abcl__othpr_002
mh_p_abcl__othpr_003
mh_p_abcl__othpr_004
mh_p_abcl__othpr_005
mh_p_abcl__othpr_006
mh_p_abcl__othpr_007
mh_p_abcl__othpr_008
mh_p_abcl__othpr_009
mh_p_abcl__othpr_010
mh_p_abcl__othpr_011
mh_p_abcl__othpr_012
mh_p_abcl__tho_005
mh_p_abcl__tho_007
Excluded values:
777
999
Validation criterion: maximally 8 of 118 items missing
compute_mh_p_abcl_tscore( data, data_norm = NULL, name = "mh_p_abcl_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 8, exclude = c("777", "999"), combine = TRUE )compute_mh_p_abcl_tscore( data, data_norm = NULL, name = "mh_p_abcl_tscore", col_age = "mh_p_abcl__cg2__age_001", col_sex = "mh_p_abcl__cg2_sex", max_na = 8, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_abcl_tscore(data) |> select( any_of(c("mh_p_abcl_tscore", vars_mh_p_abcl)) ) ## End(Not run)## Not run: compute_mh_p_abcl_tscore(data) |> select( any_of(c("mh_p_abcl_tscore", vars_mh_p_abcl)) ) ## End(Not run)
Computes the summary score mh_p_asr__afs__strng_sum
Adult Self Report [Parent] (Adaptive Functioning Scale - Personal
strength): Sum
Summarized variables:
mh_p_asr__strng_001
mh_p_asr__strng_002
mh_p_asr__strng_003
mh_p_asr__strng_004
mh_p_asr__strng_005
mh_p_asr__strng_006
mh_p_asr__strng_007
mh_p_asr__strng_008
mh_p_asr__strng_009
mh_p_asr__strng_010
mh_p_asr__strng_011
Excluded values:
777
999
Validation criterion: maximally 0 of 11 items missing
compute_mh_p_asr__afs__strng_sum( data, name = "mh_p_asr__afs__strng_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__afs__strng_sum( data, name = "mh_p_asr__afs__strng_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__afs__strng_nm()
## Not run: compute_mh_p_asr__afs__strng_sum(data) |> select( any_of(c("mh_p_asr__afs__strng_sum", vars_mh_p_asr__afs__strng)) ) ## End(Not run)## Not run: compute_mh_p_asr__afs__strng_sum(data) |> select( any_of(c("mh_p_asr__afs__strng_sum", vars_mh_p_asr__afs__strng)) ) ## End(Not run)
Computes the summary score mh_p_asr__critic_sum
Adult Self Report [Parent] (Critical Items): Sum
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_008
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__attn__inatt_002
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__rule_001
mh_p_asr__rule_003
mh_p_asr__rule__antsoc_007
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho__dep_001
Excluded values:
777
999
Validation criterion: maximally 1 of 19 items missing
compute_mh_p_asr__critic_sum( data, name = "mh_p_asr__critic_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__critic_sum( data, name = "mh_p_asr__critic_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_asr__critic_sum(data) |> select( any_of(c("mh_p_asr__critic_sum", vars_mh_p_asr__critic)) ) ## End(Not run)## Not run: compute_mh_p_asr__critic_sum(data) |> select( any_of(c("mh_p_asr__critic_sum", vars_mh_p_asr__critic)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd__hypimp_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD
Hyperactivity-Impulsivity): Sum
Summarized variables:
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_asr__dsm__adhd__hypimp_sum( data, name = "mh_p_asr__dsm__adhd__hypimp_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__adhd__hypimp_sum( data, name = "mh_p_asr__dsm__adhd__hypimp_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__adhd__hypimp_nm()
## Not run: compute_mh_p_asr__dsm__adhd__hypimp_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd__hypimp_sum", vars_mh_p_asr__dsm__adhd__hypimp)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd__hypimp_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd__hypimp_sum", vars_mh_p_asr__dsm__adhd__hypimp)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd__inatt_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention):
Sum
Summarized variables:
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_asr__dsm__adhd__inatt_sum( data, name = "mh_p_asr__dsm__adhd__inatt_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__adhd__inatt_sum( data, name = "mh_p_asr__dsm__adhd__inatt_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__adhd__inatt_nm()
## Not run: compute_mh_p_asr__dsm__adhd__inatt_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd__inatt_sum", vars_mh_p_asr__dsm__adhd__inatt)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd__inatt_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd__inatt_sum", vars_mh_p_asr__dsm__adhd__inatt)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Sum
Summarized variables:
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_asr__dsm__adhd_sum( data, name = "mh_p_asr__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__adhd_sum( data, name = "mh_p_asr__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__adhd_nm()
## Not run: compute_mh_p_asr__dsm__adhd_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd_sum", vars_mh_p_asr__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd_sum(data) |> select( any_of(c("mh_p_asr__dsm__adhd_sum", vars_mh_p_asr__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__antsoc_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Sum
Summarized variables:
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
mh_p_asr__attn__antsoc_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 1 of 20 items missing
compute_mh_p_asr__dsm__antsoc_sum( data, name = "mh_p_asr__dsm__antsoc_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__antsoc_sum( data, name = "mh_p_asr__dsm__antsoc_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__antsoc_nm()
## Not run: compute_mh_p_asr__dsm__antsoc_sum(data) |> select( any_of(c("mh_p_asr__dsm__antsoc_sum", vars_mh_p_asr__dsm__antsoc)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__antsoc_sum(data) |> select( any_of(c("mh_p_asr__dsm__antsoc_sum", vars_mh_p_asr__dsm__antsoc)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__anx_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems):
Sum
Summarized variables:
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_asr__dsm__anx_sum( data, name = "mh_p_asr__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__anx_sum( data, name = "mh_p_asr__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__anx_nm()
## Not run: compute_mh_p_asr__dsm__anx_sum(data) |> select( any_of(c("mh_p_asr__dsm__anx_sum", vars_mh_p_asr__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__anx_sum(data) |> select( any_of(c("mh_p_asr__dsm__anx_sum", vars_mh_p_asr__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__avoid_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Sum
Summarized variables:
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__othpr__avoid_001
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_asr__dsm__avoid_sum( data, name = "mh_p_asr__dsm__avoid_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__avoid_sum( data, name = "mh_p_asr__dsm__avoid_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__avoid_nm()
## Not run: compute_mh_p_asr__dsm__avoid_sum(data) |> select( any_of(c("mh_p_asr__dsm__avoid_sum", vars_mh_p_asr__dsm__avoid)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__avoid_sum(data) |> select( any_of(c("mh_p_asr__dsm__avoid_sum", vars_mh_p_asr__dsm__avoid)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__dep_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive
problems): Sum
Summarized variables:
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__tho__dep_001
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_asr__dsm__dep_sum( data, name = "mh_p_asr__dsm__dep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__dep_sum( data, name = "mh_p_asr__dsm__dep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__dep_nm()
## Not run: compute_mh_p_asr__dsm__dep_sum(data) |> select( any_of(c("mh_p_asr__dsm__dep_sum", vars_mh_p_asr__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__dep_sum(data) |> select( any_of(c("mh_p_asr__dsm__dep_sum", vars_mh_p_asr__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__somat_sum
Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
Summarized variables:
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_asr__dsm__somat_sum( data, name = "mh_p_asr__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__dsm__somat_sum( data, name = "mh_p_asr__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__dsm__somat_nm()
## Not run: compute_mh_p_asr__dsm__somat_sum(data) |> select( any_of(c("mh_p_asr__dsm__somat_sum", vars_mh_p_asr__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__somat_sum(data) |> select( any_of(c("mh_p_asr__dsm__somat_sum", vars_mh_p_asr__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__aggr_sum
Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior): Sum
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__aggr__hypimp_001
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_asr__synd__aggr_sum( data, name = "mh_p_asr__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__aggr_sum( data, name = "mh_p_asr__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__aggr_nm()
## Not run: compute_mh_p_asr__synd__aggr_sum(data) |> select( any_of(c("mh_p_asr__synd__aggr_sum", vars_mh_p_asr__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__aggr_sum(data) |> select( any_of(c("mh_p_asr__synd__aggr_sum", vars_mh_p_asr__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__anxdep_sum
Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed): Sum
Summarized variables:
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
Excluded values:
777
999
Validation criterion: maximally 1 of 18 items missing
compute_mh_p_asr__synd__anxdep_sum( data, name = "mh_p_asr__synd__anxdep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__anxdep_sum( data, name = "mh_p_asr__synd__anxdep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__anxdep_nm()
## Not run: compute_mh_p_asr__synd__anxdep_sum(data) |> select( any_of(c("mh_p_asr__synd__anxdep_sum", vars_mh_p_asr__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__anxdep_sum(data) |> select( any_of(c("mh_p_asr__synd__anxdep_sum", vars_mh_p_asr__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__attn_sum
Adult Self Report [Parent] (Syndrome Scale - Attention problems): Sum
Summarized variables:
mh_p_asr__attn_001
mh_p_asr__attn_002
mh_p_asr__attn_003
mh_p_asr__attn_004
mh_p_asr__attn_005
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__attn__antsoc_001
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_asr__synd__attn_sum( data, name = "mh_p_asr__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__attn_sum( data, name = "mh_p_asr__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__attn_nm()
## Not run: compute_mh_p_asr__synd__attn_sum(data) |> select( any_of(c("mh_p_asr__synd__attn_sum", vars_mh_p_asr__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__attn_sum(data) |> select( any_of(c("mh_p_asr__synd__attn_sum", vars_mh_p_asr__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__ext_sum
Adult Self Report [Parent] (Syndrome Scale - Externalizing): Sum
Summarized variables:
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
mh_p_asr__rule_001
mh_p_asr__rule_002
mh_p_asr__rule_003
mh_p_asr__rule_004
mh_p_asr__rule__hypimp_001
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
mh_p_asr__aggr_001
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__aggr__hypimp_001
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
Excluded values:
777
999
Validation criterion: maximally 2 of 35 items missing
compute_mh_p_asr__synd__ext_sum( data, name = "mh_p_asr__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__ext_sum( data, name = "mh_p_asr__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__ext_nm()
## Not run: compute_mh_p_asr__synd__ext_sum(data) |> select( any_of(c("mh_p_asr__synd__ext_sum", vars_mh_p_asr__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__ext_sum(data) |> select( any_of(c("mh_p_asr__synd__ext_sum", vars_mh_p_asr__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__int_sum
Adult Self Report [Parent] (Syndrome Scale - Internalizing): Sum
Summarized variables:
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
mh_p_asr__som_001
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 2 of 39 items missing
compute_mh_p_asr__synd__int_sum( data, name = "mh_p_asr__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__int_sum( data, name = "mh_p_asr__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__int_nm()
## Not run: compute_mh_p_asr__synd__int_sum(data) |> select( any_of(c("mh_p_asr__synd__int_sum", vars_mh_p_asr__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__int_sum(data) |> select( any_of(c("mh_p_asr__synd__int_sum", vars_mh_p_asr__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__intru_sum
Adult Self Report [Parent] (Syndrome Scale - Intrusive): Sum
Summarized variables:
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_p_asr__synd__intru_sum( data, name = "mh_p_asr__synd__intru_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__intru_sum( data, name = "mh_p_asr__synd__intru_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__intru_nm()
## Not run: compute_mh_p_asr__synd__intru_sum(data) |> select( any_of(c("mh_p_asr__synd__intru_sum", vars_mh_p_asr__synd__intru)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__intru_sum(data) |> select( any_of(c("mh_p_asr__synd__intru_sum", vars_mh_p_asr__synd__intru)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__othpr_sum
Adult Self Report [Parent] (Syndrome Scale - Other problems): Sum
Summarized variables:
mh_p_asr__othpr_001
mh_p_asr__othpr_002
mh_p_asr__othpr_003
mh_p_asr__othpr_004
mh_p_asr__othpr_005
mh_p_asr__othpr_006
mh_p_asr__othpr_007
mh_p_asr__othpr_008
mh_p_asr__othpr_009
mh_p_asr__othpr_010
mh_p_asr__othpr_011
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__othpr__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
mh_p_asr__othpr__avoid_001
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
Excluded values:
777
999
Validation criterion: maximally 1 of 21 items missing
compute_mh_p_asr__synd__othpr_sum( data, name = "mh_p_asr__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__othpr_sum( data, name = "mh_p_asr__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__othpr_nm()
## Not run: compute_mh_p_asr__synd__othpr_sum(data) |> select( any_of(c("mh_p_asr__synd__othpr_sum", vars_mh_p_asr__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__othpr_sum(data) |> select( any_of(c("mh_p_asr__synd__othpr_sum", vars_mh_p_asr__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__rule_sum
Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior):
Sum
Summarized variables:
mh_p_asr__rule_001
mh_p_asr__rule_002
mh_p_asr__rule_003
mh_p_asr__rule_004
mh_p_asr__rule__hypimp_001
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_asr__synd__rule_sum( data, name = "mh_p_asr__synd__rule_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__rule_sum( data, name = "mh_p_asr__synd__rule_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__rule_nm()
## Not run: compute_mh_p_asr__synd__rule_sum(data) |> select( any_of(c("mh_p_asr__synd__rule_sum", vars_mh_p_asr__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__rule_sum(data) |> select( any_of(c("mh_p_asr__synd__rule_sum", vars_mh_p_asr__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__som_sum
Adult Self Report [Parent] (Syndrome Scale - Somatic complaints): Sum
Summarized variables:
mh_p_asr__som_001
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
Excluded values:
777
999
Validation criterion: maximally 0 of 12 items missing
compute_mh_p_asr__synd__som_sum( data, name = "mh_p_asr__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__som_sum( data, name = "mh_p_asr__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__som_nm()
## Not run: compute_mh_p_asr__synd__som_sum(data) |> select( any_of(c("mh_p_asr__synd__som_sum", vars_mh_p_asr__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__som_sum(data) |> select( any_of(c("mh_p_asr__synd__som_sum", vars_mh_p_asr__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__tho_sum
Adult Self Report [Parent] (Syndrome Scale - Thought problems): Sum
Summarized variables:
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_003
mh_p_asr__tho_004
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho_008
mh_p_asr__tho__hypimp_001
mh_p_asr__tho__dep_001
Excluded values:
777
999
Validation criterion: maximally 0 of 10 items missing
compute_mh_p_asr__synd__tho_sum( data, name = "mh_p_asr__synd__tho_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__tho_sum( data, name = "mh_p_asr__synd__tho_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__tho_nm()
## Not run: compute_mh_p_asr__synd__tho_sum(data) |> select( any_of(c("mh_p_asr__synd__tho_sum", vars_mh_p_asr__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__tho_sum(data) |> select( any_of(c("mh_p_asr__synd__tho_sum", vars_mh_p_asr__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__wthdr_sum
Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Sum
Summarized variables:
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_asr__synd__wthdr_sum( data, name = "mh_p_asr__synd__wthdr_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr__synd__wthdr_sum( data, name = "mh_p_asr__synd__wthdr_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_asr__synd__wthdr_nm()
## Not run: compute_mh_p_asr__synd__wthdr_sum(data) |> select( any_of(c("mh_p_asr__synd__wthdr_sum", vars_mh_p_asr__synd__wthdr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__wthdr_sum(data) |> select( any_of(c("mh_p_asr__synd__wthdr_sum", vars_mh_p_asr__synd__wthdr)) ) ## End(Not run)
This function computes all summary scores for the mh_p_asr form. Make sure to have all necessary columns in the data frame.
compute_mh_p_asr_all(data)compute_mh_p_asr_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_asr_all(data) ## End(Not run)## Not run: compute_mh_p_asr_all(data) ## End(Not run)
Computes the summary score mh_p_asr_sum
Adult Self Report [Parent]: Sum
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_008
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__attn__inatt_002
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__rule_001
mh_p_asr__rule_003
mh_p_asr__rule__antsoc_007
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho__dep_001
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_007
mh_p_asr__attn__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__othpr__avoid_001
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_006
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__wthdr__dep_001
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__attn_001
mh_p_asr__attn_002
mh_p_asr__attn_003
mh_p_asr__attn_004
mh_p_asr__attn_005
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
mh_p_asr__rule_002
mh_p_asr__rule_004
mh_p_asr__som_001
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__othpr_001
mh_p_asr__othpr_002
mh_p_asr__othpr_003
mh_p_asr__othpr_004
mh_p_asr__othpr_005
mh_p_asr__othpr_006
mh_p_asr__othpr_007
mh_p_asr__othpr_008
mh_p_asr__othpr_009
mh_p_asr__othpr_010
mh_p_asr__othpr_011
mh_p_asr__tho_003
mh_p_asr__tho_004
mh_p_asr__tho_008
Excluded values:
777
999
Validation criterion: maximally 8 of 120 items missing
compute_mh_p_asr_sum( data, name = "mh_p_asr_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )compute_mh_p_asr_sum( data, name = "mh_p_asr_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_asr_sum(data) |> select( any_of(c("mh_p_asr_sum", vars_mh_p_asr)) ) ## End(Not run)## Not run: compute_mh_p_asr_sum(data) |> select( any_of(c("mh_p_asr_sum", vars_mh_p_asr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__adhd_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD): Sum
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_cbcl__dsm__adhd_sum( data, name = "mh_p_cbcl__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__adhd_sum( data, name = "mh_p_cbcl__dsm__adhd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__adhd_nm()
## Not run: compute_mh_p_cbcl__dsm__adhd_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_sum", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__adhd_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_sum", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__adhd_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
T-score
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_cbcl__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__adhd_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__adhd_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__adhd_nm()
## Not run: compute_mh_p_cbcl__dsm__adhd_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_tscore", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__adhd_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_tscore", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__anx_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
Sum
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_cbcl__dsm__anx_sum( data, name = "mh_p_cbcl__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__anx_sum( data, name = "mh_p_cbcl__dsm__anx_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__anx_nm()
## Not run: compute_mh_p_cbcl__dsm__anx_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_sum", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__anx_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_sum", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__anx_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
T-score
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
Excluded values:
777
999
Validation criterion: maximally 0 of 9 items missing
compute_mh_p_cbcl__dsm__anx_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__anx_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__anx_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__anx_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__anx_nm()
## Not run: compute_mh_p_cbcl__dsm__anx_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_tscore", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__anx_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_tscore", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__cond_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): Sum
Summarized variables:
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_cbcl__dsm__cond_sum( data, name = "mh_p_cbcl__dsm__cond_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__cond_sum( data, name = "mh_p_cbcl__dsm__cond_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__cond_nm()
## Not run: compute_mh_p_cbcl__dsm__cond_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_sum", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__cond_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_sum", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__cond_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): T-score
Summarized variables:
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_cbcl__dsm__cond_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__cond_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__cond_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__cond_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__cond_nm()
## Not run: compute_mh_p_cbcl__dsm__cond_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_tscore", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__cond_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_tscore", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__dep_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Sum
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_cbcl__dsm__dep_sum( data, name = "mh_p_cbcl__dsm__dep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__dep_sum( data, name = "mh_p_cbcl__dsm__dep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__dep_nm()
## Not run: compute_mh_p_cbcl__dsm__dep_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_sum", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__dep_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_sum", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__dep_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): T-score
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_cbcl__dsm__dep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__dep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__dep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__dep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__dep_nm()
## Not run: compute_mh_p_cbcl__dsm__dep_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_tscore", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__dep_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_tscore", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__opp_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): Sum
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
Excluded values:
777
999
Validation criterion: maximally 0 of 5 items missing
compute_mh_p_cbcl__dsm__opp_sum( data, name = "mh_p_cbcl__dsm__opp_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__opp_sum( data, name = "mh_p_cbcl__dsm__opp_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__opp_nm()
## Not run: compute_mh_p_cbcl__dsm__opp_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_sum", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__opp_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_sum", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__opp_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): T-score
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
Excluded values:
777
999
Validation criterion: maximally 0 of 5 items missing
compute_mh_p_cbcl__dsm__opp_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__opp_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__opp_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__opp_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__opp_nm()
## Not run: compute_mh_p_cbcl__dsm__opp_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_tscore", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__opp_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_tscore", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__somat_sum
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Sum
Summarized variables:
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_cbcl__dsm__somat_sum( data, name = "mh_p_cbcl__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__somat_sum( data, name = "mh_p_cbcl__dsm__somat_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__somat_nm()
## Not run: compute_mh_p_cbcl__dsm__somat_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_sum", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__somat_sum(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_sum", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__somat_tscore
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): T-score
Summarized variables:
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_p_cbcl__dsm__somat_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__somat_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__dsm__somat_tscore( data, data_norm = NULL, name = "mh_p_cbcl__dsm__somat_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__dsm__somat_nm()
## Not run: compute_mh_p_cbcl__dsm__somat_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_tscore", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__somat_tscore(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_tscore", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__ocd_sum
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems): Sum
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
Excluded values:
777
999
Validation criterion: maximally 0 of 8 items missing
compute_mh_p_cbcl__ocd_sum( data, name = "mh_p_cbcl__ocd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__ocd_sum( data, name = "mh_p_cbcl__ocd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__ocd_sum(data) |> select( any_of(c("mh_p_cbcl__ocd_sum", vars_mh_p_cbcl__ocd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__ocd_sum(data) |> select( any_of(c("mh_p_cbcl__ocd_sum", vars_mh_p_cbcl__ocd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__ocd_tscore
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems):
T-score
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
Excluded values:
777
999
Validation criterion: maximally 0 of 8 items missing
compute_mh_p_cbcl__ocd_tscore( data, data_norm = NULL, name = "mh_p_cbcl__ocd_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__ocd_tscore( data, data_norm = NULL, name = "mh_p_cbcl__ocd_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__ocd_tscore(data) |> select( any_of(c("mh_p_cbcl__ocd_tscore", vars_mh_p_cbcl__ocd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__ocd_tscore(data) |> select( any_of(c("mh_p_cbcl__ocd_tscore", vars_mh_p_cbcl__ocd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__sct_sum
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Sum
Summarized variables:
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
Excluded values:
777
999
Validation criterion: maximally 0 of 4 items missing
compute_mh_p_cbcl__sct_sum( data, name = "mh_p_cbcl__sct_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__sct_sum( data, name = "mh_p_cbcl__sct_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__sct_sum(data) |> select( any_of(c("mh_p_cbcl__sct_sum", vars_mh_p_cbcl__sct)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__sct_sum(data) |> select( any_of(c("mh_p_cbcl__sct_sum", vars_mh_p_cbcl__sct)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__sct_tscore
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): T-score
Summarized variables:
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
Excluded values:
777
999
Validation criterion: maximally 0 of 4 items missing
compute_mh_p_cbcl__sct_tscore( data, data_norm = NULL, name = "mh_p_cbcl__sct_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__sct_tscore( data, data_norm = NULL, name = "mh_p_cbcl__sct_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__sct_tscore(data) |> select( any_of(c("mh_p_cbcl__sct_tscore", vars_mh_p_cbcl__sct)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__sct_tscore(data) |> select( any_of(c("mh_p_cbcl__sct_tscore", vars_mh_p_cbcl__sct)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__strs_sum
Child Behavior Checklist [Parent] (Stress): Sum
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__tho_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__soc__anx_001
mh_p_cbcl__wthdep_005
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__soc_004
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_cbcl__strs_sum( data, name = "mh_p_cbcl__strs_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__strs_sum( data, name = "mh_p_cbcl__strs_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__strs_sum(data) |> select( any_of(c("mh_p_cbcl__strs_sum", vars_mh_p_cbcl__strs)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__strs_sum(data) |> select( any_of(c("mh_p_cbcl__strs_sum", vars_mh_p_cbcl__strs)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__strs_tscore
Child Behavior Checklist [Parent] (Stress): T-score
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__tho_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__soc__anx_001
mh_p_cbcl__wthdep_005
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__soc_004
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
Excluded values:
777
999
Validation criterion: maximally 0 of 14 items missing
compute_mh_p_cbcl__strs_tscore( data, data_norm = NULL, name = "mh_p_cbcl__strs_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__strs_tscore( data, data_norm = NULL, name = "mh_p_cbcl__strs_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl__strs_tscore(data) |> select( any_of(c("mh_p_cbcl__strs_tscore", vars_mh_p_cbcl__strs)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__strs_tscore(data) |> select( any_of(c("mh_p_cbcl__strs_tscore", vars_mh_p_cbcl__strs)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__aggr_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Sum
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 1 of 18 items missing
compute_mh_p_cbcl__synd__aggr_sum( data, name = "mh_p_cbcl__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__aggr_sum( data, name = "mh_p_cbcl__synd__aggr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__aggr_nm()
## Not run: compute_mh_p_cbcl__synd__aggr_sum(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_sum", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__aggr_sum(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_sum", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__aggr_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): T-score
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 1 of 18 items missing
compute_mh_p_cbcl__synd__aggr_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__aggr_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__aggr_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__aggr_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__aggr_nm()
## Not run: compute_mh_p_cbcl__synd__aggr_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_tscore", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__aggr_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_tscore", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__anxdep_sum
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Sum
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_cbcl__synd__anxdep_sum( data, name = "mh_p_cbcl__synd__anxdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__anxdep_sum( data, name = "mh_p_cbcl__synd__anxdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__anxdep_nm()
## Not run: compute_mh_p_cbcl__synd__anxdep_sum(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_sum", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__anxdep_sum(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_sum", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__anxdep_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): T-score
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 13 items missing
compute_mh_p_cbcl__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__anxdep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__anxdep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__anxdep_nm()
## Not run: compute_mh_p_cbcl__synd__anxdep_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_tscore", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__anxdep_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_tscore", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__attn_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Sum
Summarized variables:
mh_p_cbcl__attn_001
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__attn_005
Excluded values:
777
999
Validation criterion: maximally 0 of 10 items missing
compute_mh_p_cbcl__synd__attn_sum( data, name = "mh_p_cbcl__synd__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__attn_sum( data, name = "mh_p_cbcl__synd__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__attn_nm()
## Not run: compute_mh_p_cbcl__synd__attn_sum(data) |> select( any_of(c("mh_p_cbcl__synd__attn_sum", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__attn_sum(data) |> select( any_of(c("mh_p_cbcl__synd__attn_sum", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__attn_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): T-score
Summarized variables:
mh_p_cbcl__attn_001
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__attn_005
Excluded values:
777
999
Validation criterion: maximally 0 of 10 items missing
compute_mh_p_cbcl__synd__attn_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__attn_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__attn_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__attn_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__attn_nm()
## Not run: compute_mh_p_cbcl__synd__attn_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__attn_tscore", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__attn_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__attn_tscore", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__ext_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
Sum
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 2 of 35 items missing
compute_mh_p_cbcl__synd__ext_sum( data, name = "mh_p_cbcl__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__ext_sum( data, name = "mh_p_cbcl__synd__ext_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__ext_nm()
## Not run: compute_mh_p_cbcl__synd__ext_sum(data) |> select( any_of(c("mh_p_cbcl__synd__ext_sum", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__ext_sum(data) |> select( any_of(c("mh_p_cbcl__synd__ext_sum", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__ext_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
T-score
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
Validation criterion: maximally 2 of 35 items missing
compute_mh_p_cbcl__synd__ext_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__ext_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__ext_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__ext_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__ext_nm()
## Not run: compute_mh_p_cbcl__synd__ext_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__ext_tscore", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__ext_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__ext_tscore", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__int_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Sum
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 32 items missing
compute_mh_p_cbcl__synd__int_sum( data, name = "mh_p_cbcl__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__int_sum( data, name = "mh_p_cbcl__synd__int_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__int_nm()
## Not run: compute_mh_p_cbcl__synd__int_sum(data) |> select( any_of(c("mh_p_cbcl__synd__int_sum", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__int_sum(data) |> select( any_of(c("mh_p_cbcl__synd__int_sum", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__int_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
T-score
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 32 items missing
compute_mh_p_cbcl__synd__int_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__int_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__int_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__int_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__int_nm()
## Not run: compute_mh_p_cbcl__synd__int_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__int_tscore", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__int_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__int_tscore", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__othpr_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Sum
Summarized variables:
mh_p_cbcl__othpr_001
mh_p_cbcl__othpr_002
mh_p_cbcl__othpr_009
mh_p_cbcl__othpr_010
mh_p_cbcl__othpr_011
mh_p_cbcl__othpr_012
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__othpr_003
mh_p_cbcl__othpr_004
mh_p_cbcl__othpr_005
mh_p_cbcl__othpr_006
mh_p_cbcl__othpr_007
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__othpr__adhd_001
mh_p_cbcl__othpr_008
Excluded values:
777
999
Validation criterion: maximally 1 of 16 items missing
compute_mh_p_cbcl__synd__othpr_sum( data, name = "mh_p_cbcl__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__othpr_sum( data, name = "mh_p_cbcl__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__othpr_nm()
## Not run: compute_mh_p_cbcl__synd__othpr_sum(data) |> select( any_of(c("mh_p_cbcl__synd__othpr_sum", vars_mh_p_cbcl__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__othpr_sum(data) |> select( any_of(c("mh_p_cbcl__synd__othpr_sum", vars_mh_p_cbcl__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__rule_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Sum
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_cbcl__synd__rule_sum( data, name = "mh_p_cbcl__synd__rule_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__rule_sum( data, name = "mh_p_cbcl__synd__rule_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__rule_nm()
## Not run: compute_mh_p_cbcl__synd__rule_sum(data) |> select( any_of(c("mh_p_cbcl__synd__rule_sum", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__rule_sum(data) |> select( any_of(c("mh_p_cbcl__synd__rule_sum", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__rule_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): T-score
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
Excluded values:
777
999
Validation criterion: maximally 1 of 17 items missing
compute_mh_p_cbcl__synd__rule_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__rule_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__rule_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__rule_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__rule_nm()
## Not run: compute_mh_p_cbcl__synd__rule_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__rule_tscore", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__rule_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__rule_tscore", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__soc_sum
Child Behavior Checklist [Parent] (Syndrome Scale -Social): Sum
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_004
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
Excluded values:
777
999
Validation criterion: maximally 0 of 11 items missing
compute_mh_p_cbcl__synd__soc_sum( data, name = "mh_p_cbcl__synd__soc_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__soc_sum( data, name = "mh_p_cbcl__synd__soc_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__soc_nm()
## Not run: compute_mh_p_cbcl__synd__soc_sum(data) |> select( any_of(c("mh_p_cbcl__synd__soc_sum", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__soc_sum(data) |> select( any_of(c("mh_p_cbcl__synd__soc_sum", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__soc_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -Social): T-score
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_004
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
Excluded values:
777
999
Validation criterion: maximally 0 of 11 items missing
compute_mh_p_cbcl__synd__soc_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__soc_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__soc_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__soc_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__soc_nm()
## Not run: compute_mh_p_cbcl__synd__soc_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__soc_tscore", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__soc_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__soc_tscore", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__som_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Sum
Summarized variables:
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 11 items missing
compute_mh_p_cbcl__synd__som_sum( data, name = "mh_p_cbcl__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__som_sum( data, name = "mh_p_cbcl__synd__som_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__som_nm()
## Not run: compute_mh_p_cbcl__synd__som_sum(data) |> select( any_of(c("mh_p_cbcl__synd__som_sum", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__som_sum(data) |> select( any_of(c("mh_p_cbcl__synd__som_sum", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__som_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): T-score
Summarized variables:
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 0 of 11 items missing
compute_mh_p_cbcl__synd__som_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__som_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__som_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__som_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__som_nm()
## Not run: compute_mh_p_cbcl__synd__som_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__som_tscore", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__som_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__som_tscore", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__tho_sum
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Sum
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__tho__dep_001
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_007
mh_p_cbcl__tho_008
mh_p_cbcl__tho__dep_002
mh_p_cbcl__tho_009
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__tho_012
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_cbcl__synd__tho_sum( data, name = "mh_p_cbcl__synd__tho_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__tho_sum( data, name = "mh_p_cbcl__synd__tho_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__tho_nm()
## Not run: compute_mh_p_cbcl__synd__tho_sum(data) |> select( any_of(c("mh_p_cbcl__synd__tho_sum", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__tho_sum(data) |> select( any_of(c("mh_p_cbcl__synd__tho_sum", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__tho_tscore
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
T-score
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__tho__dep_001
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_007
mh_p_cbcl__tho_008
mh_p_cbcl__tho__dep_002
mh_p_cbcl__tho_009
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__tho_012
Excluded values:
777
999
Validation criterion: maximally 1 of 15 items missing
compute_mh_p_cbcl__synd__tho_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__tho_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__tho_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__tho_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__tho_nm()
## Not run: compute_mh_p_cbcl__synd__tho_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__tho_tscore", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__tho_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__tho_tscore", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__wthdep_sum
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): Sum
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 8 items missing
compute_mh_p_cbcl__synd__wthdep_sum( data, name = "mh_p_cbcl__synd__wthdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__wthdep_sum( data, name = "mh_p_cbcl__synd__wthdep_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__wthdep_nm()
## Not run: compute_mh_p_cbcl__synd__wthdep_sum(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_sum", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__wthdep_sum(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_sum", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__wthdep_tscore
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): T-score
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
Excluded values:
777
999
Validation criterion: maximally 0 of 8 items missing
compute_mh_p_cbcl__synd__wthdep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__wthdep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl__synd__wthdep_tscore( data, data_norm = NULL, name = "mh_p_cbcl__synd__wthdep_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_cbcl__synd__wthdep_nm()
## Not run: compute_mh_p_cbcl__synd__wthdep_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_tscore", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__wthdep_tscore(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_tscore", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)
This function computes all summary scores for the mh_p_cbcl form. Make sure to have all necessary columns in the data frame.
compute_mh_p_cbcl_all(data)compute_mh_p_cbcl_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_cbcl_all(data) ## End(Not run)## Not run: compute_mh_p_cbcl_all(data) ## End(Not run)
Computes the summary score mh_p_cbcl_sum
Child Behavior Checklist [Parent] (Syndrome Scale): Sum
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep_001
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
mh_p_cbcl__wthdep_005
mh_p_cbcl__soc_004
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__anxdep_002
mh_p_cbcl__attn_001
mh_p_cbcl__attn_004
mh_p_cbcl__rule_001
mh_p_cbcl__rule_006
mh_p_cbcl__rule_002
mh_p_cbcl__rule_003
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_004
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__othpr_001
mh_p_cbcl__othpr_002
mh_p_cbcl__othpr_009
mh_p_cbcl__othpr_010
mh_p_cbcl__othpr_011
mh_p_cbcl__othpr_012
mh_p_cbcl__othpr_003
mh_p_cbcl__othpr_004
mh_p_cbcl__othpr_005
mh_p_cbcl__othpr_006
mh_p_cbcl__othpr_007
mh_p_cbcl__othpr_008
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_008
mh_p_cbcl__tho_009
mh_p_cbcl__tho_012
Excluded values:
777
999
Validation criterion: maximally 8 of 119 items missing
compute_mh_p_cbcl_sum( data, name = "mh_p_cbcl_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl_sum( data, name = "mh_p_cbcl_sum", max_na = 8, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl_sum(data) |> select( any_of(c("mh_p_cbcl_sum", vars_mh_p_cbcl)) ) ## End(Not run)## Not run: compute_mh_p_cbcl_sum(data) |> select( any_of(c("mh_p_cbcl_sum", vars_mh_p_cbcl)) ) ## End(Not run)
Computes the summary score mh_p_cbcl_tscore
Child Behavior Checklist [Parent] (Syndrome Scale): T-score
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep_001
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
mh_p_cbcl__wthdep_005
mh_p_cbcl__soc_004
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__anxdep_002
mh_p_cbcl__attn_001
mh_p_cbcl__attn_004
mh_p_cbcl__rule_001
mh_p_cbcl__rule_006
mh_p_cbcl__rule_002
mh_p_cbcl__rule_003
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_004
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__othpr_001
mh_p_cbcl__othpr_002
mh_p_cbcl__othpr_009
mh_p_cbcl__othpr_010
mh_p_cbcl__othpr_011
mh_p_cbcl__othpr_012
mh_p_cbcl__othpr_003
mh_p_cbcl__othpr_004
mh_p_cbcl__othpr_005
mh_p_cbcl__othpr_006
mh_p_cbcl__othpr_007
mh_p_cbcl__othpr_008
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_008
mh_p_cbcl__tho_009
mh_p_cbcl__tho_012
Excluded values:
777
999
Validation criterion: maximally 8 of 119 items missing
compute_mh_p_cbcl_tscore( data, data_norm = NULL, name = "mh_p_cbcl_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 8, exclude = c("777", "999"), combine = TRUE )compute_mh_p_cbcl_tscore( data, data_norm = NULL, name = "mh_p_cbcl_tscore", col_age = "mh_p_cbcl_age", col_sex = "ab_g_stc__cohort_sex", max_na = 8, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_cbcl_tscore(data) |> select( any_of(c("mh_p_cbcl_tscore", vars_mh_p_cbcl)) ) ## End(Not run)## Not run: compute_mh_p_cbcl_tscore(data) |> select( any_of(c("mh_p_cbcl_tscore", vars_mh_p_cbcl)) ) ## End(Not run)
Computes the summary score mh_p_ders__attun_nm
Difficulties in Emotion Regulation Scale [Parent] (Attuned): Number
missing
Summarized variables:
mh_p_ders__attun_001
mh_p_ders__attun_002
mh_p_ders__attun_003
mh_p_ders__attun_004
mh_p_ders__attun_005
mh_p_ders__attun_006
Excluded values:
999
777
compute_mh_p_ders__attun_nm( data, name = "mh_p_ders__attun_nm", exclude = c("999", "777"), combine = TRUE )compute_mh_p_ders__attun_nm( data, name = "mh_p_ders__attun_nm", exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_ders__attun_mean()
## Not run: compute_mh_p_ders__attun_nm(data) |> select( any_of(c("mh_p_ders__attun_nm", vars_mh_p_ders__attun)) ) ## End(Not run)## Not run: compute_mh_p_ders__attun_nm(data) |> select( any_of(c("mh_p_ders__attun_nm", vars_mh_p_ders__attun)) ) ## End(Not run)
Computes the summary score mh_p_ders__catast_nm
Difficulties in Emotion Regulation Scale [Parent] (Catastrophize):
Number missing
Summarized variables:
mh_p_ders__catast_001
mh_p_ders__catast_002
mh_p_ders__catast_003
mh_p_ders__catast_004
mh_p_ders__catast_005
mh_p_ders__catast_006
mh_p_ders__catast_007
mh_p_ders__catast_008
mh_p_ders__catast_009
mh_p_ders__catast_010
mh_p_ders__catast_011
mh_p_ders__catast_012
Excluded values:
999
777
compute_mh_p_ders__catast_nm( data, name = "mh_p_ders__catast_nm", exclude = c("999", "777"), combine = TRUE )compute_mh_p_ders__catast_nm( data, name = "mh_p_ders__catast_nm", exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_ders__catast_mean()
## Not run: compute_mh_p_ders__catast_nm(data) |> select( any_of(c("mh_p_ders__catast_nm", vars_mh_p_ders__catast)) ) ## End(Not run)## Not run: compute_mh_p_ders__catast_nm(data) |> select( any_of(c("mh_p_ders__catast_nm", vars_mh_p_ders__catast)) ) ## End(Not run)
Computes the summary score mh_p_ders__distract_nm
Difficulties in Emotion Regulation Scale [Parent] (Distracted): Number
missing
Summarized variables:
mh_p_ders__distract_001
mh_p_ders__distract_002
mh_p_ders__distract_003
mh_p_ders__distract_004
Excluded values:
999
777
compute_mh_p_ders__distract_nm( data, name = "mh_p_ders__distract_nm", exclude = c("999", "777"), combine = TRUE )compute_mh_p_ders__distract_nm( data, name = "mh_p_ders__distract_nm", exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_ders__distract_mean()
## Not run: compute_mh_p_ders__distract_nm(data) |> select( any_of(c("mh_p_ders__distract_nm", vars_mh_p_ders__distract)) ) ## End(Not run)## Not run: compute_mh_p_ders__distract_nm(data) |> select( any_of(c("mh_p_ders__distract_nm", vars_mh_p_ders__distract)) ) ## End(Not run)
Computes the summary score mh_p_ders__negscnd_nm
Difficulties in Emotion Regulation Scale [Parent] (Negative
Secondary): Number missing
Summarized variables:
mh_p_ders__negscnd_001
mh_p_ders__negscnd_002
mh_p_ders__negscnd_003
mh_p_ders__negscnd_004
mh_p_ders__negscnd_005
mh_p_ders__negscnd_006
mh_p_ders__negscnd_007
Excluded values:
999
777
compute_mh_p_ders__negscnd_nm( data, name = "mh_p_ders__negscnd_nm", exclude = c("999", "777"), combine = TRUE )compute_mh_p_ders__negscnd_nm( data, name = "mh_p_ders__negscnd_nm", exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_p_ders__negscnd_mean()
## Not run: compute_mh_p_ders__negscnd_nm(data) |> select( any_of(c("mh_p_ders__negscnd_nm", vars_mh_p_ders__negscnd)) ) ## End(Not run)## Not run: compute_mh_p_ders__negscnd_nm(data) |> select( any_of(c("mh_p_ders__negscnd_nm", vars_mh_p_ders__negscnd)) ) ## End(Not run)
This function computes all summary scores for the mh_p_ders table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ders_all(data)compute_mh_p_ders_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_ders_all(data) ## End(Not run)## Not run: compute_mh_p_ders_all(data) ## End(Not run)
Computes the summary score mh_p_eatq__actv_nm
Early Adolescent Temperament Questionnaire [Parent] (Activation):
Number missing
Summarized variables:
mh_p_eatq__actv_001
mh_p_eatq__actv_002
mh_p_eatq__actv_003
mh_p_eatq__actv_004
mh_p_eatq__actv_005
mh_p_eatq__actv_006
mh_p_eatq__actv_007
Excluded values: none
compute_mh_p_eatq__actv_nm(data, name = "mh_p_eatq__actv_nm", combine = TRUE)compute_mh_p_eatq__actv_nm(data, name = "mh_p_eatq__actv_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__actv_mean()
## Not run: data <- compute_mh_p_eatq__actv_nm(data) select( data, any_of(c("mh_p_eatq__actv_nm", vars_mh_p_eatq__actv)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__actv_nm(data) select( data, any_of(c("mh_p_eatq__actv_nm", vars_mh_p_eatq__actv)) ) ## End(Not run)
Computes the summary score mh_p_eatq__affl_nm
Early Adolescent Temperament Questionnaire [Parent] (Affiliation):
Number missing
Summarized variables:
mh_p_eatq__affl_001
mh_p_eatq__affl_002
mh_p_eatq__affl_003
mh_p_eatq__affl_004
mh_p_eatq__affl_005
mh_p_eatq__affl_006
Excluded values: none
compute_mh_p_eatq__affl_nm(data, name = "mh_p_eatq__affl_nm", combine = TRUE)compute_mh_p_eatq__affl_nm(data, name = "mh_p_eatq__affl_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__affl_mean()
## Not run: data <- compute_mh_p_eatq__affl_nm(data) select( data, any_of(c("mh_p_eatq__affl_nm", vars_mh_p_eatq__affl)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__affl_nm(data) select( data, any_of(c("mh_p_eatq__affl_nm", vars_mh_p_eatq__affl)) ) ## End(Not run)
Computes the summary score mh_p_eatq__aggr_nm
Early Adolescent Temperament Questionnaire [Parent] (Aggression):
Number missing
Summarized variables:
mh_p_eatq__aggr_001
mh_p_eatq__aggr_002
mh_p_eatq__aggr_003
mh_p_eatq__aggr_004
mh_p_eatq__aggr_005
mh_p_eatq__aggr_006
mh_p_eatq__aggr_007
Excluded values: none
compute_mh_p_eatq__aggr_nm(data, name = "mh_p_eatq__aggr_nm", combine = TRUE)compute_mh_p_eatq__aggr_nm(data, name = "mh_p_eatq__aggr_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__aggr_mean()
## Not run: data <- compute_mh_p_eatq__aggr_nm(data) select( data, any_of(c("mh_p_eatq__aggr_nm", vars_mh_p_eatq__aggr)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__aggr_nm(data) select( data, any_of(c("mh_p_eatq__aggr_nm", vars_mh_p_eatq__aggr)) ) ## End(Not run)
Computes the summary score mh_p_eatq__attn_nm
Early Adolescent Temperament Questionnaire [Parent] (Attention):
Number missing
Summarized variables:
mh_p_eatq__attn_001
mh_p_eatq__attn_002
mh_p_eatq__attn_003
mh_p_eatq__attn_004
mh_p_eatq__attn_005
mh_p_eatq__attn_006
Excluded values: none
compute_mh_p_eatq__attn_nm(data, name = "mh_p_eatq__attn_nm", combine = TRUE)compute_mh_p_eatq__attn_nm(data, name = "mh_p_eatq__attn_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__attn_mean()
## Not run: data <- compute_mh_p_eatq__attn_nm(data) select( data, any_of(c("mh_p_eatq__attn_nm", vars_mh_p_eatq__attn)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__attn_nm(data) select( data, any_of(c("mh_p_eatq__attn_nm", vars_mh_p_eatq__attn)) ) ## End(Not run)
Computes the summary score mh_p_eatq__depm_nm
Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood):
Number missing
Summarized variables:
mh_p_eatq__depm_001
mh_p_eatq__depm_002
mh_p_eatq__depm_003
mh_p_eatq__depm_004
mh_p_eatq__depm_005
Excluded values: none
compute_mh_p_eatq__depm_nm(data, name = "mh_p_eatq__depm_nm", combine = TRUE)compute_mh_p_eatq__depm_nm(data, name = "mh_p_eatq__depm_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__depm_mean()
## Not run: data <- compute_mh_p_eatq__depm_nm(data) select( data, any_of(c("mh_p_eatq__depm_nm", vars_mh_p_eatq__depm)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__depm_nm(data) select( data, any_of(c("mh_p_eatq__depm_nm", vars_mh_p_eatq__depm)) ) ## End(Not run)
Computes the summary score mh_p_eatq__fear_nm
Early Adolescent Temperament Questionnaire [Parent] (Fear): Number
missing
Summarized variables:
mh_p_eatq__fear_001
mh_p_eatq__fear_002
mh_p_eatq__fear_003
mh_p_eatq__fear_004
mh_p_eatq__fear_005
mh_p_eatq__fear_006
Excluded values: none
compute_mh_p_eatq__fear_nm(data, name = "mh_p_eatq__fear_nm", combine = TRUE)compute_mh_p_eatq__fear_nm(data, name = "mh_p_eatq__fear_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__fear_mean()
## Not run: data <- compute_mh_p_eatq__fear_nm(data) select( data, any_of(c("mh_p_eatq__fear_nm", vars_mh_p_eatq__fear)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__fear_nm(data) select( data, any_of(c("mh_p_eatq__fear_nm", vars_mh_p_eatq__fear)) ) ## End(Not run)
Computes the summary score mh_p_eatq__frust_nm
Early Adolescent Temperament Questionnaire [Parent] (Frustration):
Number missing
Summarized variables:
mh_p_eatq__frust_001
mh_p_eatq__frust_002
mh_p_eatq__frust_003
mh_p_eatq__frust_004
mh_p_eatq__frust_005
mh_p_eatq__frust_006
Excluded values: none
compute_mh_p_eatq__frust_nm(data, name = "mh_p_eatq__frust_nm", combine = TRUE)compute_mh_p_eatq__frust_nm(data, name = "mh_p_eatq__frust_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__frust_mean()
## Not run: data <- compute_mh_p_eatq__frust_nm(data) select( data, any_of(c("mh_p_eatq__frust_nm", vars_mh_p_eatq__frust)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__frust_nm(data) select( data, any_of(c("mh_p_eatq__frust_nm", vars_mh_p_eatq__frust)) ) ## End(Not run)
Computes the summary score mh_p_eatq__inhib_nm
Early Adolescent Temperament Questionnaire [Parent] (Inhibition):
Number missing
Summarized variables:
mh_p_eatq__inhib_001
mh_p_eatq__inhib_002
mh_p_eatq__inhib_003
mh_p_eatq__inhib_004
mh_p_eatq__inhib_005
Excluded values: none
compute_mh_p_eatq__inhib_nm(data, name = "mh_p_eatq__inhib_nm", combine = TRUE)compute_mh_p_eatq__inhib_nm(data, name = "mh_p_eatq__inhib_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__inhib_mean()
## Not run: data <- compute_mh_p_eatq__inhib_nm(data) select( data, any_of(c("mh_p_eatq__inhib_nm", vars_mh_p_eatq__inhib)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__inhib_nm(data) select( data, any_of(c("mh_p_eatq__inhib_nm", vars_mh_p_eatq__inhib)) ) ## End(Not run)
Computes the summary score mh_p_eatq__shy_nm
Early Adolescent Temperament Questionnaire [Parent] (Shyness): Number
missing
Summarized variables:
mh_p_eatq__shy_001
mh_p_eatq__shy_002
mh_p_eatq__shy_003
mh_p_eatq__shy_004
mh_p_eatq__shy_005
Excluded values: none
compute_mh_p_eatq__shy_nm(data, name = "mh_p_eatq__shy_nm", combine = TRUE)compute_mh_p_eatq__shy_nm(data, name = "mh_p_eatq__shy_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__shy_nm(data) select( data, any_of(c("mh_p_eatq__shy_nm", vars_mh_p_eatq__shy)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__shy_nm(data) select( data, any_of(c("mh_p_eatq__shy_nm", vars_mh_p_eatq__shy)) ) ## End(Not run)
Computes the summary score mh_p_eatq__ss__efcon_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Effortful control: Combines attention, inhibition, and activation scales):
Mean
Summarized variables:
mh_p_eatq__attn_mean
mh_p_eatq__inhib_mean
mh_p_eatq__actv_mean
Excluded values: none
compute_mh_p_eatq__ss__efcon_mean( data, name = "mh_p_eatq__ss__efcon_mean", combine = TRUE )compute_mh_p_eatq__ss__efcon_mean( data, name = "mh_p_eatq__ss__efcon_mean", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Effortful Control = Attention, Inhibitory Control, Activation Control
In the super scale calculation, no NA is allowed.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_p_eatq__ss__efcon_mean(data) |> select( any_of(c( "mh_p_eatq__ss__efcon_mean", )) ) ## End(Not run)## Not run: compute_mh_p_eatq__ss__efcon_mean(data) |> select( any_of(c( "mh_p_eatq__ss__efcon_mean", )) ) ## End(Not run)
Computes the summary score mh_p_eatq__ss__efcon_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Effortful control: Combines attention, inhibition, and activation scales):
Number missing
Summarized variables:
mh_p_eatq__attn_001
mh_p_eatq__attn_002
mh_p_eatq__attn_003
mh_p_eatq__attn_004
mh_p_eatq__attn_005
mh_p_eatq__attn_006
mh_p_eatq__inhib_001
mh_p_eatq__inhib_002
mh_p_eatq__inhib_003
mh_p_eatq__inhib_004
mh_p_eatq__inhib_005
mh_p_eatq__actv_001
mh_p_eatq__actv_002
mh_p_eatq__actv_003
mh_p_eatq__actv_004
mh_p_eatq__actv_005
mh_p_eatq__actv_006
mh_p_eatq__actv_007
Excluded values: none
compute_mh_p_eatq__ss__efcon_nm( data, name = "mh_p_eatq__ss__efcon_nm", combine = TRUE )compute_mh_p_eatq__ss__efcon_nm( data, name = "mh_p_eatq__ss__efcon_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__ss__efcon_mean()
## Not run: data <- compute_mh_p_eatq__ss__efcon_nm(data) ## End(Not run)## Not run: data <- compute_mh_p_eatq__ss__efcon_nm(data) ## End(Not run)
Computes the summary score mh_p_eatq__ss__negaff_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Negative Affect: Combines frustration, depressed mood, and aggression
scales): Mean
Summarized variables:
mh_p_eatq__frust_mean
mh_p_eatq__depm_mean
mh_p_eatq__aggr_mean
Excluded values: none
compute_mh_p_eatq__ss__negaff_mean( data, name = "mh_p_eatq__ss__negaff_mean", combine = TRUE )compute_mh_p_eatq__ss__negaff_mean( data, name = "mh_p_eatq__ss__negaff_mean", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Negative Affect = Frustration, Depressive Mood, Aggression
In the super scale calculation, no NA is allowed.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data |> compute_mh_p_eatq__ss__negaff_mean() |> select( any_of(c( "mh_p_eatq__ss__negaff_mean" )) ) ## End(Not run)## Not run: data |> compute_mh_p_eatq__ss__negaff_mean() |> select( any_of(c( "mh_p_eatq__ss__negaff_mean" )) ) ## End(Not run)
Computes the summary score mh_p_eatq__ss__negaff_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Negative Affect: Combines frustration, depressed mood, and aggression
scales): Number missing
Summarized variables:
mh_p_eatq__frust_001
mh_p_eatq__frust_002
mh_p_eatq__frust_003
mh_p_eatq__frust_004
mh_p_eatq__frust_005
mh_p_eatq__frust_006
mh_p_eatq__depm_001
mh_p_eatq__depm_002
mh_p_eatq__depm_003
mh_p_eatq__depm_004
mh_p_eatq__depm_005
mh_p_eatq__aggr_001
mh_p_eatq__aggr_002
mh_p_eatq__aggr_003
mh_p_eatq__aggr_004
mh_p_eatq__aggr_005
mh_p_eatq__aggr_006
mh_p_eatq__aggr_007
Excluded values: none
compute_mh_p_eatq__ss__negaff_nm( data, name = "mh_p_eatq__ss__negaff_nm", combine = TRUE )compute_mh_p_eatq__ss__negaff_nm( data, name = "mh_p_eatq__ss__negaff_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__ss__negaff_mean()
## Not run: data <- compute_mh_p_eatq__ss__negaff_nm(data) ## End(Not run)## Not run: data <- compute_mh_p_eatq__ss__negaff_nm(data) ## End(Not run)
Computes the summary score mh_p_eatq__ss__surg_mean
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Surgency: Combines surgency, fear (reverse coded), and shyness (reverse
coded) scales): Mean [Validation: No more than 0 missing or declined]
Summarized variables:
mh_p_eatq__surg_mean
mh_p_eatq__fear_mean (revert)
mh_p_eatq__shy_mean (revert)
Excluded values: none
compute_mh_p_eatq__ss__surg_mean( data, name = "mh_p_eatq__ss__surg_mean", combine = TRUE )compute_mh_p_eatq__ss__surg_mean( data, name = "mh_p_eatq__ss__surg_mean", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, append the new computed column to the end
of original tibble? Default is |
Surgency = Surgency, Fear (reverse scored), Shyness (reverse scored)
In the super scale calculation, no NA is allowed.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_p_eatq__ss__surg_mean(data) |> select( any_of(c( "mh_p_eatq__ss__surg_mean" )) ) ## End(Not run)## Not run: compute_mh_p_eatq__ss__surg_mean(data) |> select( any_of(c( "mh_p_eatq__ss__surg_mean" )) ) ## End(Not run)
Computes the summary score mh_p_eatq__ss__surg_nm
Early Adolescent Temperament Questionnaire [Parent] (Super scale -
Surgency: Combines surgency, fear (reverse coded), and shyness (reverse
coded) scales): Number missing
Summarized variables:
mh_p_eatq__surg_001
mh_p_eatq__surg_002
mh_p_eatq__surg_003
mh_p_eatq__surg_004
mh_p_eatq__surg_005
mh_p_eatq__surg_006
mh_p_eatq__surg_007
mh_p_eatq__surg_008
mh_p_eatq__surg_009
mh_p_eatq__fear_001
mh_p_eatq__fear_002
mh_p_eatq__fear_003
mh_p_eatq__fear_004
mh_p_eatq__fear_005
mh_p_eatq__fear_006
mh_p_eatq__shy_001
mh_p_eatq__shy_002
mh_p_eatq__shy_003
mh_p_eatq__shy_004
mh_p_eatq__shy_005
Excluded values: none
compute_mh_p_eatq__ss__surg_nm( data, name = "mh_p_eatq__ss__surg_nm", combine = TRUE )compute_mh_p_eatq__ss__surg_nm( data, name = "mh_p_eatq__ss__surg_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__ss__surg_mean()
## Not run: data <- compute_mh_p_eatq__ss__surg_nm(data) ## End(Not run)## Not run: data <- compute_mh_p_eatq__ss__surg_nm(data) ## End(Not run)
Computes the summary score mh_p_eatq__surg_nm
Early Adolescent Temperament Questionnaire [Parent] (Surgency): Number
missing
Summarized variables:
mh_p_eatq__surg_001
mh_p_eatq__surg_002
mh_p_eatq__surg_003
mh_p_eatq__surg_004
mh_p_eatq__surg_005
mh_p_eatq__surg_006
mh_p_eatq__surg_007
mh_p_eatq__surg_008
mh_p_eatq__surg_009
Excluded values: none
compute_mh_p_eatq__surg_nm(data, name = "mh_p_eatq__surg_nm", combine = TRUE)compute_mh_p_eatq__surg_nm(data, name = "mh_p_eatq__surg_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_mh_p_eatq__surg_mean()
## Not run: data <- compute_mh_p_eatq__surg_nm(data) select( data, any_of(c("mh_p_eatq__surg_nm", vars_mh_p_eatq__surg)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__surg_nm(data) select( data, any_of(c("mh_p_eatq__surg_nm", vars_mh_p_eatq__surg)) ) ## End(Not run)
This super function computes all scores in EATQ using all the default arguments.
compute_mh_p_eatq_all(data)compute_mh_p_eatq_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
Make sure the data is the full set of all variables from EATQ
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_eatq_all(data) ## End(Not run)## Not run: compute_mh_p_eatq_all(data) ## End(Not run)
mh_p_famhx summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_mh_p_famhx_all(data)compute_mh_p_famhx_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_famhx_all(data) ## End(Not run)## Not run: compute_mh_p_famhx_all(data) ## End(Not run)
This function computes all summary scores for the mh_p_gbi table. Make sure to have all necessary columns in the data frame.
compute_mh_p_gbi_all(data)compute_mh_p_gbi_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_gbi_all(data) ## End(Not run)## Not run: compute_mh_p_gbi_all(data) ## End(Not run)
Computes the summary score mh_p_gbi_sum
Parent General Behavior Inventory [Parent]: Sum
Summarized variables:
mh_p_gbi_001
mh_p_gbi_002
mh_p_gbi_003
mh_p_gbi_004
mh_p_gbi_005
mh_p_gbi_006
mh_p_gbi_007
mh_p_gbi_008
mh_p_gbi_009
mh_p_gbi_010
Excluded values: none
Validation criterion: none of 10 items missing
compute_mh_p_gbi_sum( data, name = "mh_p_gbi_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_p_gbi_sum( data, name = "mh_p_gbi_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_gbi_sum(data) |> select( any_of(c("mh_p_gbi_sum", vars_mh_p_gbi)) ) ## End(Not run)## Not run: compute_mh_p_gbi_sum(data) |> select( any_of(c("mh_p_gbi_sum", vars_mh_p_gbi)) ) ## End(Not run)
This function computes all summary scores for the mh_p_ksads__adhd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__adhd_all(data)compute_mh_p_ksads__adhd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__agor table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__agor_all(data)compute_mh_p_ksads__agor_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__asd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__asd_all(data)compute_mh_p_ksads__asd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__bpd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__bpd_all(data)compute_mh_p_ksads__bpd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__cond table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__cond_all(data)compute_mh_p_ksads__cond_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__dep table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__dep_all(data)compute_mh_p_ksads__dep_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__dep table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__dmdd_all(data)compute_mh_p_ksads__dmdd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__ed table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__ed_all(data)compute_mh_p_ksads__ed_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__gad table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__gad_all(data)compute_mh_p_ksads__gad_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__hom table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__hom_all(data)compute_mh_p_ksads__hom_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__ocd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__ocd_all(data)compute_mh_p_ksads__ocd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__odd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__odd_all(data)compute_mh_p_ksads__odd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__panic table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__panic_all(data)compute_mh_p_ksads__panic_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__phobia table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__phobia_all(data)compute_mh_p_ksads__phobia_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__psych table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__psych_all(data)compute_mh_p_ksads__psych_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__ptsd table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__ptsd_all(data)compute_mh_p_ksads__ptsd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__sepanx table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__sepanx_all(data)compute_mh_p_ksads__sepanx_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__sleep table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__sleep_all(data)compute_mh_p_ksads__sleep_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__socanx table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__socanx_all(data)compute_mh_p_ksads__socanx_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__suic table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__suic_all(data)compute_mh_p_ksads__suic_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_p_ksads__tic table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ksads__tic_all(data)compute_mh_p_ksads__tic_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
Computes the summary score mh_p_ple__exp__bad_count
Life Events [Parent] (Experience Bad Events): Count
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
Excluded values:
444
777
999
compute_mh_p_ple__exp__bad_count( data, name = "mh_p_ple__exp__bad_count", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__bad_count( data, name = "mh_p_ple__exp__bad_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__bad_count__v01
Life Events [Parent] (Experience Bad Events): Count - Version 1 (Year
3)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
Excluded values:
444
777
999
compute_mh_p_ple__exp__bad_count__v01( data, name = "mh_p_ple__exp__bad_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__bad_count__v01( data, name = "mh_p_ple__exp__bad_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__bad_count__v02
Life Events [Parent] (Experience Bad Events): Count - Version 2 (Year
4 and Year 5)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
Excluded values:
444
777
999
compute_mh_p_ple__exp__bad_count__v02( data, name = "mh_p_ple__exp__bad_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__bad_count__v02( data, name = "mh_p_ple__exp__bad_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__bad_count__v03
Life Events [Parent] (Experience Bad Events): Count - Version 3 (Year
6)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp__bad_count__v03( data, name = "mh_p_ple__exp__bad_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__bad_count__v03( data, name = "mh_p_ple__exp__bad_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__bad_count__v04
Life Events [Parent] (Experience Bad Events): Count - Version 4
(Starting at Year 7)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp__bad_count__v04( data, name = "mh_p_ple__exp__bad_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__bad_count__v04( data, name = "mh_p_ple__exp__bad_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__good_count
Life Events [Parent] (Experience Good Events): Count
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
Excluded values:
444
777
999
compute_mh_p_ple__exp__good_count( data, name = "mh_p_ple__exp__good_count", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__good_count( data, name = "mh_p_ple__exp__good_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__good_count__v01
Life Events [Parent] (Experience Good Events): Count - Version 1 (Year
3)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
Excluded values:
444
777
999
compute_mh_p_ple__exp__good_count__v01( data, name = "mh_p_ple__exp__good_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__good_count__v01( data, name = "mh_p_ple__exp__good_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__good_count__v02
Life Events [Parent] (Experience Good Events): Count - Version 2 (Year
4 and Year 5)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
Excluded values:
444
777
999
compute_mh_p_ple__exp__good_count__v02( data, name = "mh_p_ple__exp__good_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__good_count__v02( data, name = "mh_p_ple__exp__good_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__good_count__v03
Life Events [Parent] (Experience Good Events): Count - Version 3 (Year
6)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp__good_count__v03( data, name = "mh_p_ple__exp__good_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__good_count__v03( data, name = "mh_p_ple__exp__good_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp__good_count__v04
Life Events [Parent] (Experience Good Events): Count - Version 4
(Starting at Year 7)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp__good_count__v04( data, name = "mh_p_ple__exp__good_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )compute_mh_p_ple__exp__good_count__v04( data, name = "mh_p_ple__exp__good_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp_nm
Life Events [Parent] (Experience): Number missing
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
Excluded values:
444
777
999
compute_mh_p_ple__exp_nm(data, name = "mh_p_ple__exp_nm", combine = TRUE)compute_mh_p_ple__exp_nm(data, name = "mh_p_ple__exp_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp_nm__v01
Life Events [Parent] (Experience): Number missing - Version 1 (Year 3)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
Excluded values:
444
777
999
compute_mh_p_ple__exp_nm__v01( data, name = "mh_p_ple__exp_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_p_ple__exp_nm__v01( data, name = "mh_p_ple__exp_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp_nm__v02
Life Events [Parent] (Experience): Number missing - Version 2 (Year 4
and Year 5)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
Excluded values:
444
777
999
compute_mh_p_ple__exp_nm__v02( data, name = "mh_p_ple__exp_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_p_ple__exp_nm__v02( data, name = "mh_p_ple__exp_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp_nm__v03
Life Events [Parent] (Experience): Number missing - Version 3 (Year
6 )
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp_nm__v03( data, name = "mh_p_ple__exp_nm__v03", events = "ses-06A", combine = TRUE )compute_mh_p_ple__exp_nm__v03( data, name = "mh_p_ple__exp_nm__v03", events = "ses-06A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__exp_nm__v04
Life Events [Parent] (Experience): Number missing - Version 4
(Starting at Year 7)
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
Excluded values:
444
777
999
compute_mh_p_ple__exp_nm__v04( data, name = "mh_p_ple__exp_nm__v04", events = "ses-07A", combine = TRUE )compute_mh_p_ple__exp_nm__v04( data, name = "mh_p_ple__exp_nm__v04", events = "ses-07A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_mean
Life Events [Parent] (Severity of Bad Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_p_ple__severity__bad_mean( data, name = "mh_p_ple__severity__bad_mean", combine = TRUE, max_na = 5 )compute_mh_p_ple__severity__bad_mean( data, name = "mh_p_ple__severity__bad_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_mean__v01
Life Events [Parent] (Severity of Bad Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_p_ple__severity__bad_mean__v01( data, name = "mh_p_ple__severity__bad_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_mean__v01( data, name = "mh_p_ple__severity__bad_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_mean__v02
Life Events [Parent] (Severity of Bad Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
compute_mh_p_ple__severity__bad_mean__v02( data, name = "mh_p_ple__severity__bad_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_mean__v02( data, name = "mh_p_ple__severity__bad_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_mean__v03
Life Events [Parent] (Severity of Bad Events): Mean - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_p_ple__severity__bad_mean__v03( data, name = "mh_p_ple__severity__bad_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_mean__v03( data, name = "mh_p_ple__severity__bad_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_mean__v04
Life Events [Parent] (Severity of Bad Events): Mean - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
compute_mh_p_ple__severity__bad_mean__v04( data, name = "mh_p_ple__severity__bad_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )compute_mh_p_ple__severity__bad_mean__v04( data, name = "mh_p_ple__severity__bad_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_sum
Life Events [Parent] (Severity of Bad Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_p_ple__severity__bad_sum( data, name = "mh_p_ple__severity__bad_sum", combine = TRUE, max_na = 5 )compute_mh_p_ple__severity__bad_sum( data, name = "mh_p_ple__severity__bad_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_sum__v01
Life Events [Parent] (Severity of Bad Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_p_ple__severity__bad_sum__v01( data, name = "mh_p_ple__severity__bad_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_sum__v01( data, name = "mh_p_ple__severity__bad_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_sum__v02
Life Events [Parent] (Severity of Bad Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
compute_mh_p_ple__severity__bad_sum__v02( data, name = "mh_p_ple__severity__bad_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_sum__v02( data, name = "mh_p_ple__severity__bad_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_sum__v03
Life Events [Parent] (Severity of Bad Events): Sum - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_p_ple__severity__bad_sum__v03( data, name = "mh_p_ple__severity__bad_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__bad_sum__v03( data, name = "mh_p_ple__severity__bad_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__bad_sum__v04
Life Events [Parent] (Severity of Bad Events): Sum - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
compute_mh_p_ple__severity__bad_sum__v04( data, name = "mh_p_ple__severity__bad_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )compute_mh_p_ple__severity__bad_sum__v04( data, name = "mh_p_ple__severity__bad_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_mean
Life Events [Parent] (Severity of Good Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_p_ple__severity__good_mean( data, name = "mh_p_ple__severity__good_mean", combine = TRUE, max_na = 5 )compute_mh_p_ple__severity__good_mean( data, name = "mh_p_ple__severity__good_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_mean__v01
Life Events [Parent] (Severity of Good Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_p_ple__severity__good_mean__v01( data, name = "mh_p_ple__severity__good_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__good_mean__v01( data, name = "mh_p_ple__severity__good_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_mean__v02
Life Events [Parent] (Severity of Good Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
compute_mh_p_ple__severity__good_mean__v02( data, name = "mh_p_ple__severity__good_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__good_mean__v02( data, name = "mh_p_ple__severity__good_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_mean__v03
Life Events [Parent] (Severity of Good Events): Mean - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_p_ple__severity__good_mean__v03( data, name = "mh_p_ple__severity__good_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity__good_mean__v03( data, name = "mh_p_ple__severity__good_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_mean__v04
Life Events [Parent] (Severity of Good Events): Mean - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
compute_mh_p_ple__severity__good_mean__v04( data, name = "mh_p_ple__severity__good_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )compute_mh_p_ple__severity__good_mean__v04( data, name = "mh_p_ple__severity__good_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_sum
Life Events [Parent] (Severity of Good Events): Sum [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_p_ple__severity__good_sum( data, name = "mh_p_ple__severity__good_sum", combine = TRUE, max_na = 5 )compute_mh_p_ple__severity__good_sum( data, name = "mh_p_ple__severity__good_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_mean
Life Events [Parent] (Severity): Mean [Validation: No more than 5
events missing and no severity items missing or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_p_ple__severity_mean( data, name = "mh_p_ple__severity_mean", combine = TRUE, max_na = 5 )compute_mh_p_ple__severity_mean( data, name = "mh_p_ple__severity_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_mean__v01
Life Events [Parent] (Severity): Mean - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_p_ple__severity_mean__v01( data, name = "mh_p_ple__severity_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity_mean__v01( data, name = "mh_p_ple__severity_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_mean__v02
Life Events [Parent] (Severity): Mean - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
compute_mh_p_ple__severity_mean__v02( data, name = "mh_p_ple__severity_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_p_ple__severity_mean__v02( data, name = "mh_p_ple__severity_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_mean__v03
Life Events [Parent] (Severity): Mean - Version 3 (Year 6 )
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_p_ple__severity_mean__v03( data, name = "mh_p_ple__severity_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )compute_mh_p_ple__severity_mean__v03( data, name = "mh_p_ple__severity_mean__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_mean__v04
Life Events [Parent] (Severity): Mean - Version 4 (Starting at Year 7)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
compute_mh_p_ple__severity_mean__v04( data, name = "mh_p_ple__severity_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )compute_mh_p_ple__severity_mean__v04( data, name = "mh_p_ple__severity_mean__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_nm
Life Events [Parent] (Severity): Number missing
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
compute_mh_p_ple__severity_nm( data, name = "mh_p_ple__severity_nm", combine = TRUE )compute_mh_p_ple__severity_nm( data, name = "mh_p_ple__severity_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_nm__v01
Life Events [Parent] (Severity): Number missing - Version 1 (Year 3)
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
compute_mh_p_ple__severity_nm__v01( data, name = "mh_p_ple__severity_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_p_ple__severity_nm__v01( data, name = "mh_p_ple__severity_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_nm__v02
Life Events [Parent] (Severity): Number missing - Version 2 (Year 4
and Year 5)
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
compute_mh_p_ple__severity_nm__v02( data, name = "mh_p_ple__severity_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_p_ple__severity_nm__v02( data, name = "mh_p_ple__severity_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_nm__v03
Life Events [Parent] (Severity): Number missing - Version 3 (Year 6 )
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
compute_mh_p_ple__severity_nm__v03( data, name = "mh_p_ple__severity_nm__v03", events = "ses-06A", combine = TRUE )compute_mh_p_ple__severity_nm__v03( data, name = "mh_p_ple__severity_nm__v03", events = "ses-06A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_nm__v04
Life Events [Parent] (Severity): Number missing - Version 4 (Starting
at Year 7)
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
compute_mh_p_ple__severity_nm__v04( data, name = "mh_p_ple__severity_nm__v04", events = "ses-07A", combine = TRUE )compute_mh_p_ple__severity_nm__v04( data, name = "mh_p_ple__severity_nm__v04", events = "ses-07A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the mh_p_ple form. Make sure to have all necessary columns in the data frame.
compute_mh_p_ple_all(data)compute_mh_p_ple_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_ple_all(data) ## End(Not run)## Not run: compute_mh_p_ple_all(data) ## End(Not run)
Computes the summary score mh_p_ple_nm
Life Events [Parent] (Events): Number missing
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
Excluded values:
444
777
999
compute_mh_p_ple_nm(data, name = "mh_p_ple_nm", combine = TRUE)compute_mh_p_ple_nm(data, name = "mh_p_ple_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_nm__v01
Life Events [Parent] (Events): Number missing - Version 1 (Year 3)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
Excluded values:
444
777
999
compute_mh_p_ple_nm__v01( data, name = "mh_p_ple_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_p_ple_nm__v01( data, name = "mh_p_ple_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_nm__v02
Life Events [Parent] (Events): Number missing - Version 2 (Year 4 and
Year 5)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
mh_p_ple_032
Excluded values:
444
777
999
compute_mh_p_ple_nm__v02( data, name = "mh_p_ple_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_p_ple_nm__v02( data, name = "mh_p_ple_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_nm__v03
Life Events [Parent] (Events): Number missing - Version 3 (Year 6 )
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
mh_p_ple_032
mh_p_ple_033
Excluded values:
444
777
999
compute_mh_p_ple_nm__v03( data, name = "mh_p_ple_nm__v03", events = "ses-06A", combine = TRUE )compute_mh_p_ple_nm__v03( data, name = "mh_p_ple_nm__v03", events = "ses-06A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_nm__v04
Life Events [Parent] (Events): Number missing - Version 4 (Starting at
Year 7)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_007
mh_p_ple_008
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_018
mh_p_ple_019
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_032
mh_p_ple_033
Excluded values:
444
777
999
compute_mh_p_ple_nm__v04( data, name = "mh_p_ple_nm__v04", events = "ses-07A", combine = TRUE )compute_mh_p_ple_nm__v04( data, name = "mh_p_ple_nm__v04", events = "ses-07A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the mh_p_ssrs table. Make sure to have all necessary columns in the data frame.
compute_mh_p_ssrs_all(data)compute_mh_p_ssrs_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_p_ssrs_all(data) ## End(Not run)## Not run: compute_mh_p_ssrs_all(data) ## End(Not run)
Computes the summary score mh_p_ssrs_sum
Short Social Responsiveness Scale [Parent]: Sum
Summarized variables:
mh_p_ssrs_001
mh_p_ssrs_002
mh_p_ssrs_003
mh_p_ssrs_004
mh_p_ssrs_005
mh_p_ssrs_006
mh_p_ssrs_007
mh_p_ssrs_008
mh_p_ssrs_009
mh_p_ssrs_010
mh_p_ssrs_011
Excluded values: none
Validation criterion: none of 11 items missing
compute_mh_p_ssrs_sum( data, name = "mh_p_ssrs_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_p_ssrs_sum( data, name = "mh_p_ssrs_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_p_ssrs_sum(data) |> select( any_of(c("mh_p_ssrs_sum", vars_mh_p_ssrs)) ) ## End(Not run)## Not run: compute_mh_p_ssrs_sum(data) |> select( any_of(c("mh_p_ssrs_sum", vars_mh_p_ssrs)) ) ## End(Not run)
Computes the summary score mh_t_bpm__attn_sum
Brief Problem Monitor [Teacher] (Attention): Sum
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__attn_sum( data, name = "mh_t_bpm__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__attn_sum( data, name = "mh_t_bpm__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__attn_sum(data) |> select( any_of(c("mh_t_bpm__attn_sum", vars_mh_t_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_t_bpm__attn_sum(data) |> select( any_of(c("mh_t_bpm__attn_sum", vars_mh_t_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_t_bpm__attn_tscore
Brief Problem Monitor [Teacher] (Attention): T-score
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__attn_tscore( data, data_norm = NULL, name = "mh_t_bpm__attn_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__attn_tscore( data, data_norm = NULL, name = "mh_t_bpm__attn_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__attn_tscore(data) |> select( any_of(c("mh_t_bpm__attn_tscore", vars_mh_t_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_t_bpm__attn_tscore(data) |> select( any_of(c("mh_t_bpm__attn_tscore", vars_mh_t_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_t_bpm__ext_sum
Brief Problem Monitor [Teacher] (Externalizing): Sum
Summarized variables:
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__ext_sum( data, name = "mh_t_bpm__ext_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__ext_sum( data, name = "mh_t_bpm__ext_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__ext_sum(data) |> select( any_of(c("mh_t_bpm__ext_sum", vars_mh_t_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_t_bpm__ext_sum(data) |> select( any_of(c("mh_t_bpm__ext_sum", vars_mh_t_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_t_bpm__ext_tscore
Brief Problem Monitor [Teacher] (Externalizing): T-score
Summarized variables:
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__ext_tscore( data, data_norm = NULL, name = "mh_t_bpm__ext_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__ext_tscore( data, data_norm = NULL, name = "mh_t_bpm__ext_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__ext_tscore(data) |> select( any_of(c("mh_t_bpm__ext_tscore", vars_mh_t_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_t_bpm__ext_tscore(data) |> select( any_of(c("mh_t_bpm__ext_tscore", vars_mh_t_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_t_bpm__int_sum
Brief Problem Monitor [Teacher] (Internalizing): Sum
Summarized variables:
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__int_sum( data, name = "mh_t_bpm__int_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__int_sum( data, name = "mh_t_bpm__int_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__int_sum(data) |> select( any_of(c("mh_t_bpm__int_sum", vars_mh_t_bpm__int)) ) ## End(Not run)## Not run: compute_mh_t_bpm__int_sum(data) |> select( any_of(c("mh_t_bpm__int_sum", vars_mh_t_bpm__int)) ) ## End(Not run)
Computes the summary score mh_t_bpm__int_tscore
Brief Problem Monitor [Teacher] (Internalizing): T-score
Summarized variables:
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_t_bpm__int_tscore( data, data_norm = NULL, name = "mh_t_bpm__int_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm__int_tscore( data, data_norm = NULL, name = "mh_t_bpm__int_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm__int_tscore(data) |> select( any_of(c("mh_t_bpm__int_tscore", vars_mh_t_bpm__int)) ) ## End(Not run)## Not run: compute_mh_t_bpm__int_tscore(data) |> select( any_of(c("mh_t_bpm__int_tscore", vars_mh_t_bpm__int)) ) ## End(Not run)
This function computes all summary scores for the mh_t_bpm form. Make sure to have all necessary columns in the data frame.
compute_mh_t_bpm_all(data)compute_mh_t_bpm_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_t_bpm_all(data) ## End(Not run)## Not run: compute_mh_t_bpm_all(data) ## End(Not run)
Computes the summary score mh_t_bpm_sum
Brief Problem Monitor [Teacher]: Sum
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 1 of 18 items missing
compute_mh_t_bpm_sum( data, name = "mh_t_bpm_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm_sum( data, name = "mh_t_bpm_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm_sum(data) |> select( any_of(c("mh_t_bpm_sum", vars_mh_t_bpm)) ) ## End(Not run)## Not run: compute_mh_t_bpm_sum(data) |> select( any_of(c("mh_t_bpm_sum", vars_mh_t_bpm)) ) ## End(Not run)
Computes the summary score mh_t_bpm_tscore
Brief Problem Monitor [Teacher]: T-score
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 1 of 18 items missing
compute_mh_t_bpm_tscore( data, data_norm = NULL, name = "mh_t_bpm_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_t_bpm_tscore( data, data_norm = NULL, name = "mh_t_bpm_tscore", col_age = "mh_t_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_t_bpm_tscore(data) |> select( any_of(c("mh_t_bpm_tscore", vars_mh_t_bpm)) ) ## End(Not run)## Not run: compute_mh_t_bpm_tscore(data) |> select( any_of(c("mh_t_bpm_tscore", vars_mh_t_bpm)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__dr_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Drive): Sum
Summarized variables:
mh_y_bisbas__bas__dr_001
mh_y_bisbas__bas__dr_002
mh_y_bisbas__bas__dr_003
mh_y_bisbas__bas__dr_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_bisbas__bas__dr_sum( data, name = "mh_y_bisbas__bas__dr_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bas__dr_sum( data, name = "mh_y_bisbas__bas__dr_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_bisbas__bas__dr_nm()
## Not run: compute_mh_y_bisbas__bas__dr_sum(data) |> select( any_of(c("mh_y_bisbas__bas__dr_sum", vars_mh_y_bisbas__bas__dr)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__dr_sum(data) |> select( any_of(c("mh_y_bisbas__bas__dr_sum", vars_mh_y_bisbas__bas__dr)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__fs_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Fun Seeking): Sum
Summarized variables:
mh_y_bisbas__bas__fs_001
mh_y_bisbas__bas__fs_002
mh_y_bisbas__bas__fs_003
mh_y_bisbas__bas__fs_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_bisbas__bas__fs_sum( data, name = "mh_y_bisbas__bas__fs_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bas__fs_sum( data, name = "mh_y_bisbas__bas__fs_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_bisbas__bas__fs_nm()
## Not run: compute_mh_y_bisbas__bas__fs_sum(data) |> select( any_of(c("mh_y_bisbas__bas__fs_sum", vars_mh_y_bisbas__bas__fs)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__fs_sum(data) |> select( any_of(c("mh_y_bisbas__bas__fs_sum", vars_mh_y_bisbas__bas__fs)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__rr_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Reward Responsiveness): Sum
Summarized variables:
mh_y_bisbas__bas__rr_001
mh_y_bisbas__bas__rr_002
mh_y_bisbas__bas__rr_003
mh_y_bisbas__bas__rr_004
mh_y_bisbas__bas__rr_005
Excluded values: none
Validation criterion: none of 5 items missing
compute_mh_y_bisbas__bas__rr_sum( data, name = "mh_y_bisbas__bas__rr_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bas__rr_sum( data, name = "mh_y_bisbas__bas__rr_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_bisbas__bas__rr_nm()
## Not run: compute_mh_y_bisbas__bas__rr_sum(data) |> select( any_of(c("mh_y_bisbas__bas__rr_sum", vars_mh_y_bisbas__bas__rr)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__rr_sum(data) |> select( any_of(c("mh_y_bisbas__bas__rr_sum", vars_mh_y_bisbas__bas__rr)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__rr_sum__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] ((BAS Reward Responsiveness (modified)): Sum
Summarized variables:
mh_y_bisbas__bas__rr_001
mh_y_bisbas__bas__rr_002
mh_y_bisbas__bas__rr_004
mh_y_bisbas__bas__rr_005
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_bisbas__bas__rr_sum__v01( data, name = "mh_y_bisbas__bas__rr_sum__v01", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bas__rr_sum__v01( data, name = "mh_y_bisbas__bas__rr_sum__v01", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_bisbas__bas__rr_nm__v01()
## Not run: compute_mh_y_bisbas__bas__rr_sum__v01(data) |> select( any_of(c("mh_y_bisbas__bas__rr_sum__v01", vars_mh_y_bisbas__bas__rr__v01)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__rr_sum__v01(data) |> select( any_of(c("mh_y_bisbas__bas__rr_sum__v01", vars_mh_y_bisbas__bas__rr__v01)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bis_sum
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS): Sum
Summarized variables:
mh_y_bisbas__bis_001
mh_y_bisbas__bis_002
mh_y_bisbas__bis_003
mh_y_bisbas__bis_004
mh_y_bisbas__bis_005
mh_y_bisbas__bis_006
mh_y_bisbas__bis_007
Excluded values: none
Validation criterion: none of 7 items missing
compute_mh_y_bisbas__bis_sum( data, name = "mh_y_bisbas__bis_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bis_sum( data, name = "mh_y_bisbas__bis_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bisbas__bis_sum(data) |> select( any_of(c("mh_y_bisbas__bis_sum", vars_mh_y_bisbas__bis)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bis_sum(data) |> select( any_of(c("mh_y_bisbas__bis_sum", vars_mh_y_bisbas__bis)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bis_sum__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS (modified)): Sum
Summarized variables:
mh_y_bisbas__bis_002
mh_y_bisbas__bis_003
mh_y_bisbas__bis_004
mh_y_bisbas__bis_006
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_bisbas__bis_sum__v01( data, name = "mh_y_bisbas__bis_sum__v01", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_bisbas__bis_sum__v01( data, name = "mh_y_bisbas__bis_sum__v01", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_bisbas__bis_nm__v01()
## Not run: compute_mh_y_bisbas__bis_sum__v01(data) |> select( any_of(c("mh_y_bisbas__bis_sum__v01", vars_mh_y_bisbas__bis__v01)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bis_sum__v01(data) |> select( any_of(c("mh_y_bisbas__bis_sum__v01", vars_mh_y_bisbas__bis__v01)) ) ## End(Not run)
This function computes all summary scores for the mh_y_bisbas table. Make sure to have all necessary columns in the data frame.
compute_mh_y_bisbas_all(data)compute_mh_y_bisbas_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_bisbas_all(data) ## End(Not run)## Not run: compute_mh_y_bisbas_all(data) ## End(Not run)
Computes the summary score mh_y_bpm__attn_sum
Brief Problem Monitor [Youth] (Attention): Sum
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_y_bpm__attn_sum( data, name = "mh_y_bpm__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__attn_sum( data, name = "mh_y_bpm__attn_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__attn_sum(data) |> select( any_of(c("mh_y_bpm__attn_sum", vars_mh_y_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_y_bpm__attn_sum(data) |> select( any_of(c("mh_y_bpm__attn_sum", vars_mh_y_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_y_bpm__attn_tscore
Brief Problem Monitor [Youth] (Attention): T-score
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_y_bpm__attn_tscore( data, data_norm = NULL, name = "mh_y_bpm__attn_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__attn_tscore( data, data_norm = NULL, name = "mh_y_bpm__attn_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__attn_tscore(data) |> select( any_of(c("mh_y_bpm__attn_tscore", vars_mh_y_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_y_bpm__attn_tscore(data) |> select( any_of(c("mh_y_bpm__attn_tscore", vars_mh_y_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_y_bpm__ext_sum
Brief Problem Monitor [Youth] (Externalizing): Sum
Summarized variables:
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_y_bpm__ext_sum( data, name = "mh_y_bpm__ext_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__ext_sum( data, name = "mh_y_bpm__ext_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__ext_sum(data) |> select( any_of(c("mh_y_bpm__ext_sum", vars_mh_y_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_y_bpm__ext_sum(data) |> select( any_of(c("mh_y_bpm__ext_sum", vars_mh_y_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_y_bpm__ext_tscore
Brief Problem Monitor [Youth] (Externalizing): T-score
Summarized variables:
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_y_bpm__ext_tscore( data, data_norm = NULL, name = "mh_y_bpm__ext_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__ext_tscore( data, data_norm = NULL, name = "mh_y_bpm__ext_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__ext_tscore(data) |> select( any_of(c("mh_y_bpm__ext_tscore", vars_mh_y_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_y_bpm__ext_tscore(data) |> select( any_of(c("mh_y_bpm__ext_tscore", vars_mh_y_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_y_bpm__int_sum
Brief Problem Monitor [Youth] (Internalizing): Sum
Summarized variables:
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_y_bpm__int_sum( data, name = "mh_y_bpm__int_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__int_sum( data, name = "mh_y_bpm__int_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__int_sum(data) |> select( any_of(c("mh_y_bpm__int_sum", vars_mh_y_bpm__int)) ) ## End(Not run)## Not run: compute_mh_y_bpm__int_sum(data) |> select( any_of(c("mh_y_bpm__int_sum", vars_mh_y_bpm__int)) ) ## End(Not run)
Computes the summary score mh_y_bpm__int_tscore
Brief Problem Monitor [Youth] (Internalizing): T-score
Summarized variables:
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 0 of 6 items missing
compute_mh_y_bpm__int_tscore( data, data_norm = NULL, name = "mh_y_bpm__int_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm__int_tscore( data, data_norm = NULL, name = "mh_y_bpm__int_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm__int_tscore(data) |> select( any_of(c("mh_y_bpm__int_tscore", vars_mh_y_bpm__int)) ) ## End(Not run)## Not run: compute_mh_y_bpm__int_tscore(data) |> select( any_of(c("mh_y_bpm__int_tscore", vars_mh_y_bpm__int)) ) ## End(Not run)
This function computes all summary scores for the mh_y_bpm form. Make sure to have all necessary columns in the data frame.
compute_mh_y_bpm_all(data)compute_mh_y_bpm_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_bpm_all(data) ## End(Not run)## Not run: compute_mh_y_bpm_all(data) ## End(Not run)
Computes the summary score mh_y_bpm_sum
Brief Problem Monitor [Youth]: Sum
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 1 of 19 items missing
compute_mh_y_bpm_sum( data, name = "mh_y_bpm_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm_sum( data, name = "mh_y_bpm_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm_sum(data) |> select( any_of(c("mh_y_bpm_sum", vars_mh_y_bpm)) ) ## End(Not run)## Not run: compute_mh_y_bpm_sum(data) |> select( any_of(c("mh_y_bpm_sum", vars_mh_y_bpm)) ) ## End(Not run)
Computes the summary score mh_y_bpm_tscore
Brief Problem Monitor [Youth]: T-score
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
Validation criterion: maximally 1 of 19 items missing
compute_mh_y_bpm_tscore( data, data_norm = NULL, name = "mh_y_bpm_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_bpm_tscore( data, data_norm = NULL, name = "mh_y_bpm_tscore", col_age = "mh_y_bpm_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_bpm_tscore(data) |> select( any_of(c("mh_y_bpm_tscore", vars_mh_y_bpm)) ) ## End(Not run)## Not run: compute_mh_y_bpm_tscore(data) |> select( any_of(c("mh_y_bpm_tscore", vars_mh_y_bpm)) ) ## End(Not run)
Computes the summary score mh_y_erq__reapp_nm
Emotion Regulation Questionnaire [Youth] (Reappraisal): Number missing
Summarized variables:
mh_y_erq__reapp_001
mh_y_erq__reapp_002
mh_y_erq__reapp_003
Excluded values:
777
compute_mh_y_erq__reapp_nm( data, name = "mh_y_erq__reapp_nm", exclude = c("777"), combine = TRUE )compute_mh_y_erq__reapp_nm( data, name = "mh_y_erq__reapp_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_erq__reapp_mean()
## Not run: compute_mh_y_erq__reapp_nm(data) |> select( any_of(c("mh_y_erq__reapp_nm", vars_mh_y_erq__reapp)) ) ## End(Not run)## Not run: compute_mh_y_erq__reapp_nm(data) |> select( any_of(c("mh_y_erq__reapp_nm", vars_mh_y_erq__reapp)) ) ## End(Not run)
Computes the summary score mh_y_erq__suppr_nm
Emotion Regulation Questionnaire [Youth] (Suppression): Number missing
Summarized variables:
mh_y_erq__suppr_001
mh_y_erq__suppr_002
mh_y_erq__suppr_003
Excluded values:
777
compute_mh_y_erq__suppr_nm( data, name = "mh_y_erq__suppr_nm", exclude = c("777"), combine = TRUE )compute_mh_y_erq__suppr_nm( data, name = "mh_y_erq__suppr_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_erq__suppr_mean()
## Not run: compute_mh_y_erq__suppr_nm(data) |> select( any_of(c("mh_y_erq__suppr_nm", vars_mh_y_erq__suppr)) ) ## End(Not run)## Not run: compute_mh_y_erq__suppr_nm(data) |> select( any_of(c("mh_y_erq__suppr_nm", vars_mh_y_erq__suppr)) ) ## End(Not run)
This function computes all summary scores for the mh_y_erq table. Make sure to have all necessary columns in the data frame.
compute_mh_y_erq_all(data)compute_mh_y_erq_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_erq_all(data) ## End(Not run)## Not run: compute_mh_y_erq_all(data) ## End(Not run)
This function computes all summary scores for the mh_y_ksads__bpd table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__bpd_all(data)compute_mh_y_ksads__bpd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__cond table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__cond_all(data)compute_mh_y_ksads__cond_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__dep table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__dep_all(data)compute_mh_y_ksads__dep_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__dep table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__dmdd_all(data)compute_mh_y_ksads__dmdd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__ed table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__ed_all(data)compute_mh_y_ksads__ed_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__gad table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__gad_all(data)compute_mh_y_ksads__gad_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__ocd table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__ocd_all(data)compute_mh_y_ksads__ocd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__panic table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__panic_all(data)compute_mh_y_ksads__panic_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__ptsd table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__ptsd_all(data)compute_mh_y_ksads__ptsd_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__sleep table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__sleep_all(data)compute_mh_y_ksads__sleep_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__socanx table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__socanx_all(data)compute_mh_y_ksads__socanx_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_ksads__suic table. Make sure to have all necessary columns in the data frame.
compute_mh_y_ksads__suic_all(data)compute_mh_y_ksads__suic_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the mh_y_pai table. Make sure to have all necessary columns in the data frame.
compute_mh_y_pai_all(data)compute_mh_y_pai_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_pai_all(data) ## End(Not run)## Not run: compute_mh_y_pai_all(data) ## End(Not run)
Computes the summary score mh_y_pai_sum
NIH Toolbox - Positive Affect Items [Youth] (NA): Sum [Validation:
None missing or declined]
Summarized variables:
mh_y_pai_001
mh_y_pai_002
mh_y_pai_003
mh_y_pai_004
mh_y_pai_005
mh_y_pai_006
mh_y_pai_007
mh_y_pai_008
mh_y_pai_009
Excluded values:
777
999
Validation criterion: none of 9 items missing
compute_mh_y_pai_sum( data, name = "mh_y_pai_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )compute_mh_y_pai_sum( data, name = "mh_y_pai_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_pai_sum(data) |> select( any_of(c("mh_y_pai_sum", vars_mh_y_pai)) ) ## End(Not run)## Not run: compute_mh_y_pai_sum(data) |> select( any_of(c("mh_y_pai_sum", vars_mh_y_pai)) ) ## End(Not run)
Computes the summary score mh_y_peq__overt__agg_sum
Peer Experiences Questionnaire [Youth] (Overt Aggression): Sum
Summarized variables:
mh_y_peq__overt__agg_001
mh_y_peq__overt__agg_002
mh_y_peq__overt__agg_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__overt__agg_sum( data, name = "mh_y_peq__overt__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__overt__agg_sum( data, name = "mh_y_peq__overt__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__overt__agg_nm()
## Not run: compute_mh_y_peq__overt__agg_sum(data) |> select( any_of(c("mh_y_peq__overt__agg_sum", vars_mh_y_peq__overt__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__overt__agg_sum(data) |> select( any_of(c("mh_y_peq__overt__agg_sum", vars_mh_y_peq__overt__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__overt__vict_sum
Peer Experiences Questionnaire [Youth] (Overt Victimization): Sum
Summarized variables:
mh_y_peq__overt__vict_001
mh_y_peq__overt__vict_002
mh_y_peq__overt__vict_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__overt__vict_sum( data, name = "mh_y_peq__overt__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__overt__vict_sum( data, name = "mh_y_peq__overt__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__overt__vict_nm()
## Not run: compute_mh_y_peq__overt__vict_sum(data) |> select( any_of(c("mh_y_peq__overt__vict_sum", vars_mh_y_peq__overt__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__overt__vict_sum(data) |> select( any_of(c("mh_y_peq__overt__vict_sum", vars_mh_y_peq__overt__vict)) ) ## End(Not run)
Computes the summary score mh_y_peq__rel__agg_sum
Peer Experiences Questionnaire [Youth] (Relational Aggression): Sum
Summarized variables:
mh_y_peq__rel__agg_001
mh_y_peq__rel__agg_002
mh_y_peq__rel__agg_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__rel__agg_sum( data, name = "mh_y_peq__rel__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__rel__agg_sum( data, name = "mh_y_peq__rel__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__rel__agg_nm()
## Not run: compute_mh_y_peq__rel__agg_sum(data) |> select( any_of(c("mh_y_peq__rel__agg_sum", vars_mh_y_peq__rel__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__rel__agg_sum(data) |> select( any_of(c("mh_y_peq__rel__agg_sum", vars_mh_y_peq__rel__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__rel__vict_sum
Peer Experiences Questionnaire [Youth] (Relational Victimization): Sum
Summarized variables:
mh_y_peq__rel__vict_001
mh_y_peq__rel__vict_002
mh_y_peq__rel__vict_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__rel__vict_sum( data, name = "mh_y_peq__rel__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__rel__vict_sum( data, name = "mh_y_peq__rel__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__rel__vict_nm()
## Not run: compute_mh_y_peq__rel__vict_sum(data) |> select( any_of(c("mh_y_peq__rel__vict_sum", vars_mh_y_peq__rel__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__rel__vict_sum(data) |> select( any_of(c("mh_y_peq__rel__vict_sum", vars_mh_y_peq__rel__vict)) ) ## End(Not run)
Computes the summary score mh_y_peq__rep__agg_sum
Peer Experiences Questionnaire [Youth] (Reputational Aggression): Sum
Summarized variables:
mh_y_peq__rep__agg_001
mh_y_peq__rep__agg_002
mh_y_peq__rep__agg_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__rep__agg_sum( data, name = "mh_y_peq__rep__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__rep__agg_sum( data, name = "mh_y_peq__rep__agg_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__rep__agg_nm()
## Not run: compute_mh_y_peq__rep__agg_sum(data) |> select( any_of(c("mh_y_peq__rep__agg_sum", vars_mh_y_peq__rep__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__rep__agg_sum(data) |> select( any_of(c("mh_y_peq__rep__agg_sum", vars_mh_y_peq__rep__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__rep__vict_sum
Peer Experiences Questionnaire [Youth] (Reputational Victimization):
Sum
Summarized variables:
mh_y_peq__rep__vict_001
mh_y_peq__rep__vict_002
mh_y_peq__rep__vict_003
Excluded values:
777
Validation criterion: none of 3 items missing
compute_mh_y_peq__rep__vict_sum( data, name = "mh_y_peq__rep__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )compute_mh_y_peq__rep__vict_sum( data, name = "mh_y_peq__rep__vict_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_peq__rep__vict_nm()
## Not run: compute_mh_y_peq__rep__vict_sum(data) |> select( any_of(c("mh_y_peq__rep__vict_sum", vars_mh_y_peq__rep__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__rep__vict_sum(data) |> select( any_of(c("mh_y_peq__rep__vict_sum", vars_mh_y_peq__rep__vict)) ) ## End(Not run)
This function computes all summary scores for the mh_y_peq table. Make sure to have all necessary columns in the data frame.
compute_mh_y_peq_all(data)compute_mh_y_peq_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_peq_all(data) ## End(Not run)## Not run: compute_mh_y_peq_all(data) ## End(Not run)
Computes the summary score mh_y_ple__exp__bad_count
Life Events [Youth] (Experience Bad Events): Count
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
Excluded values:
444
777
999
compute_mh_y_ple__exp__bad_count( data, name = "mh_y_ple__exp__bad_count", combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__bad_count( data, name = "mh_y_ple__exp__bad_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__bad_count__v01
Life Events [Youth] (Experience Bad Events): Count - Version 1 (Year
3)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
Excluded values:
444
777
999
compute_mh_y_ple__exp__bad_count__v01( data, name = "mh_y_ple__exp__bad_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__bad_count__v01( data, name = "mh_y_ple__exp__bad_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__bad_count__v02
Life Events [Youth] (Experience Bad Events): Count - Version 2 (Year
4 and Year 5)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
Excluded values:
444
777
999
compute_mh_y_ple__exp__bad_count__v02( data, name = "mh_y_ple__exp__bad_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__bad_count__v02( data, name = "mh_y_ple__exp__bad_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__bad_count__v03
Life Events [Youth] (Experience Bad Events): Count - Version 3
(Starting at Year 6)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
Excluded values:
444
777
999
compute_mh_y_ple__exp__bad_count__v03( data, name = "mh_y_ple__exp__bad_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__bad_count__v03( data, name = "mh_y_ple__exp__bad_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__good_count
Life Events [Youth] (Experience Good Events): Count
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
Excluded values:
444
777
999
compute_mh_y_ple__exp__good_count( data, name = "mh_y_ple__exp__good_count", combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__good_count( data, name = "mh_y_ple__exp__good_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__good_count__v01
Life Events [Youth] (Experience Good Events): Count - Version 1 (Year
3)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
Excluded values:
444
777
999
compute_mh_y_ple__exp__good_count__v01( data, name = "mh_y_ple__exp__good_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__good_count__v01( data, name = "mh_y_ple__exp__good_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__good_count__v02
Life Events [Youth] (Experience Good Events): Count - Version 2 (Year
4 and Year 5)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
Excluded values:
444
777
999
compute_mh_y_ple__exp__good_count__v02( data, name = "mh_y_ple__exp__good_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__good_count__v02( data, name = "mh_y_ple__exp__good_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp__good_count__v03
Life Events [Youth] (Experience Good Events): Count - Version 3
(Starting at Year 6)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
Excluded values:
444
777
999
compute_mh_y_ple__exp__good_count__v03( data, name = "mh_y_ple__exp__good_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )compute_mh_y_ple__exp__good_count__v03( data, name = "mh_y_ple__exp__good_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp_nm
Life Events [Youth] (Experience): Number missing
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
Excluded values:
444
777
999
compute_mh_y_ple__exp_nm(data, name = "mh_y_ple__exp_nm", combine = TRUE)compute_mh_y_ple__exp_nm(data, name = "mh_y_ple__exp_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp_nm__v01
Life Events [Youth] (Experience): Number missing - Version 1 (Year 3)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
Excluded values:
444
777
999
compute_mh_y_ple__exp_nm__v01( data, name = "mh_y_ple__exp_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_y_ple__exp_nm__v01( data, name = "mh_y_ple__exp_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp_nm__v02
Life Events [Youth] (Experience): Number missing - Version 2 (Year 4
and Year 5)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
Excluded values:
444
777
999
compute_mh_y_ple__exp_nm__v02( data, name = "mh_y_ple__exp_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_y_ple__exp_nm__v02( data, name = "mh_y_ple__exp_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__exp_nm__v03
Life Events [Youth] (Experience): Number missing - Version 3 (Starting
at Year 6)
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
Excluded values:
444
777
999
compute_mh_y_ple__exp_nm__v03( data, name = "mh_y_ple__exp_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )compute_mh_y_ple__exp_nm__v03( data, name = "mh_y_ple__exp_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_mean
Life Events [Youth] (Severity of Bad Events): Mean [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_y_ple__severity__bad_mean( data, name = "mh_y_ple__severity__bad_mean", combine = TRUE, max_na = 5 )compute_mh_y_ple__severity__bad_mean( data, name = "mh_y_ple__severity__bad_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_mean__v01
Life Events [Youth] (Severity of Bad Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_y_ple__severity__bad_mean__v01( data, name = "mh_y_ple__severity__bad_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_mean__v01( data, name = "mh_y_ple__severity__bad_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_mean__v02
Life Events [Youth] (Severity of Bad Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__bad_mean__v02( data, name = "mh_y_ple__severity__bad_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_mean__v02( data, name = "mh_y_ple__severity__bad_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_mean__v03
Life Events [Youth] (Severity of Bad Events): Mean - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__bad_mean__v03( data, name = "mh_y_ple__severity__bad_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_mean__v03( data, name = "mh_y_ple__severity__bad_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_sum
Life Events [Youth] (Severity of Bad Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_y_ple__severity__bad_sum( data, name = "mh_y_ple__severity__bad_sum", combine = TRUE, max_na = 5 )compute_mh_y_ple__severity__bad_sum( data, name = "mh_y_ple__severity__bad_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_sum__v01
Life Events [Youth] (Severity of Bad Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_y_ple__severity__bad_sum__v01( data, name = "mh_y_ple__severity__bad_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_sum__v01( data, name = "mh_y_ple__severity__bad_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_sum__v02
Life Events [Youth] (Severity of Bad Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__bad_sum__v02( data, name = "mh_y_ple__severity__bad_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_sum__v02( data, name = "mh_y_ple__severity__bad_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__bad_sum__v03
Life Events [Youth] (Severity of Bad Events): Sum - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__bad_sum__v03( data, name = "mh_y_ple__severity__bad_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__bad_sum__v03( data, name = "mh_y_ple__severity__bad_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_mean
Life Events [Youth] (Severity of Good Events): Mean [Validation:
No more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_y_ple__severity__good_mean( data, name = "mh_y_ple__severity__good_mean", combine = TRUE, max_na = 5 )compute_mh_y_ple__severity__good_mean( data, name = "mh_y_ple__severity__good_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_mean__v01
Life Events [Youth] (Severity of Good Events): Mean - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_y_ple__severity__good_mean__v01( data, name = "mh_y_ple__severity__good_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__good_mean__v01( data, name = "mh_y_ple__severity__good_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_mean__v02
Life Events [Youth] (Severity of Good Events): Mean - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__good_mean__v02( data, name = "mh_y_ple__severity__good_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__good_mean__v02( data, name = "mh_y_ple__severity__good_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_mean__v03
Life Events [Youth] (Severity of Good Events): Mean - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity__good_mean__v03( data, name = "mh_y_ple__severity__good_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity__good_mean__v03( data, name = "mh_y_ple__severity__good_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_mean
Life Events [Youth] (Severity): Mean [Validation: No more than 5
events missing and no severity items missing or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
compute_mh_y_ple__severity_mean( data, name = "mh_y_ple__severity_mean", combine = TRUE, max_na = 5 )compute_mh_y_ple__severity_mean( data, name = "mh_y_ple__severity_mean", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_mean__v01
Life Events [Youth] (Severity): Mean - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
compute_mh_y_ple__severity_mean__v01( data, name = "mh_y_ple__severity_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )compute_mh_y_ple__severity_mean__v01( data, name = "mh_y_ple__severity_mean__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_mean__v02
Life Events [Youth] (Severity): Mean - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
compute_mh_y_ple__severity_mean__v02( data, name = "mh_y_ple__severity_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity_mean__v02( data, name = "mh_y_ple__severity_mean__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_mean__v03
Life Events [Youth] (Severity): Mean - Version 3 (Starting at Year 6)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 34 items missing
compute_mh_y_ple__severity_mean__v03( data, name = "mh_y_ple__severity_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )compute_mh_y_ple__severity_mean__v03( data, name = "mh_y_ple__severity_mean__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_nm
Life Events [Youth] (Severity): Number missing
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
compute_mh_y_ple__severity_nm( data, name = "mh_y_ple__severity_nm", combine = TRUE )compute_mh_y_ple__severity_nm( data, name = "mh_y_ple__severity_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_nm__v01
Life Events [Youth] (Severity): Number missing - Version 1 (Year 3)
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
compute_mh_y_ple__severity_nm__v01( data, name = "mh_y_ple__severity_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_y_ple__severity_nm__v01( data, name = "mh_y_ple__severity_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_nm__v02
Life Events [Youth] (Severity): Number missing - Version 2 (Year 4 and
Year 5)
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
compute_mh_y_ple__severity_nm__v02( data, name = "mh_y_ple__severity_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_y_ple__severity_nm__v02( data, name = "mh_y_ple__severity_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_nm__v03
Life Events [Youth] (Severity): Number missing - Version 3 (Starting
at Year 6)
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
mh_y_ple__severity_034
Excluded values:
444
777
999
compute_mh_y_ple__severity_nm__v03( data, name = "mh_y_ple__severity_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )compute_mh_y_ple__severity_nm__v03( data, name = "mh_y_ple__severity_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the mh_y_ple form. Make sure to have all necessary columns in the data frame.
compute_mh_y_ple_all(data)compute_mh_y_ple_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_ple_all(data) ## End(Not run)## Not run: compute_mh_y_ple_all(data) ## End(Not run)
Computes the summary score mh_y_ple_nm
Life Events [Youth] (Events): Number missing
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
Excluded values:
444
777
999
compute_mh_y_ple_nm(data, name = "mh_y_ple_nm", combine = TRUE)compute_mh_y_ple_nm(data, name = "mh_y_ple_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_nm__v01
Life Events [Youth] (Events): Number missing - Version 1 (Year 3)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
Excluded values:
444
777
999
compute_mh_y_ple_nm__v01( data, name = "mh_y_ple_nm__v01", events = "ses-03A", combine = TRUE )compute_mh_y_ple_nm__v01( data, name = "mh_y_ple_nm__v01", events = "ses-03A", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_nm__v02
Life Events [Youth] (Events): Number missing - Version 2 (Year 4 and
Year 5)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
mh_y_ple_032
mh_y_ple_034
Excluded values:
444
777
999
compute_mh_y_ple_nm__v02( data, name = "mh_y_ple_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )compute_mh_y_ple_nm__v02( data, name = "mh_y_ple_nm__v02", events = c("ses-04A", "ses-05A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_nm__v03
Life Events [Youth] (Events): Number missing - Version 3 (Starting at
Year 6)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
mh_y_ple_032
mh_y_ple_033
mh_y_ple_034
Excluded values:
444
777
999
compute_mh_y_ple_nm__v03( data, name = "mh_y_ple_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )compute_mh_y_ple_nm__v03( data, name = "mh_y_ple_nm__v03", events = c("ses-06A", "ses-07A"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_pps__bother__no_count
Prodromal Psychosis Scale [Youth] (Bother
Summarized variables:
mh_y_pps__bother_001
mh_y_pps__bother_002
mh_y_pps__bother_003
mh_y_pps__bother_004
mh_y_pps__bother_005
mh_y_pps__bother_006
mh_y_pps__bother_007
mh_y_pps__bother_008
mh_y_pps__bother_009
mh_y_pps__bother_010
mh_y_pps__bother_011
mh_y_pps__bother_012
mh_y_pps__bother_013
mh_y_pps__bother_014
mh_y_pps__bother_015
mh_y_pps__bother_016
mh_y_pps__bother_017
mh_y_pps__bother_018
mh_y_pps__bother_019
mh_y_pps__bother_020
mh_y_pps__bother_021
Excluded values: none
Validation criterion: 0 of 21 items missing
compute_mh_y_pps__bother__no_count( data, name = "mh_y_pps__bother__no_count", max_na = 0, combine = TRUE )compute_mh_y_pps__bother__no_count( data, name = "mh_y_pps__bother__no_count", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
The bother count is depend on the mh_y_pps__bother_nm score. If the
mh_y_pps__bother_nm score is greater than max_na, the bother count
is set to NA.
There is also a sanity check for the gating question in PPS bother score.
If the paired gating question is 0 or NA and the bother score is not
missing, the paired bother score is set to NA before computing the count.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_y_pps__bother__no_count(data) |> select( any_of(c("mh_y_pps__bother__no_count", vars_mh_y_pps__bother)) ) ## End(Not run)## Not run: compute_mh_y_pps__bother__no_count(data) |> select( any_of(c("mh_y_pps__bother__no_count", vars_mh_y_pps__bother)) ) ## End(Not run)
Computes the summary score mh_y_pps__bother__yes_count
Prodromal Psychosis Scale [Youth] (Bother
Summarized variables:
mh_y_pps__bother_001
mh_y_pps__bother_002
mh_y_pps__bother_003
mh_y_pps__bother_004
mh_y_pps__bother_005
mh_y_pps__bother_006
mh_y_pps__bother_007
mh_y_pps__bother_008
mh_y_pps__bother_009
mh_y_pps__bother_010
mh_y_pps__bother_011
mh_y_pps__bother_012
mh_y_pps__bother_013
mh_y_pps__bother_014
mh_y_pps__bother_015
mh_y_pps__bother_016
mh_y_pps__bother_017
mh_y_pps__bother_018
mh_y_pps__bother_019
mh_y_pps__bother_020
mh_y_pps__bother_021
Excluded values: none
Validation criterion: 0 of 21 items missing
compute_mh_y_pps__bother__yes_count( data, name = "mh_y_pps__bother__yes_count", max_na = 0, combine = TRUE )compute_mh_y_pps__bother__yes_count( data, name = "mh_y_pps__bother__yes_count", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
The bother count is depend on the mh_y_pps__bother_nm score. If the
mh_y_pps__bother_nm score is greater than max_na, the bother count
is set to NA.
There is also a sanity check for the gating question in PPS bother score.
If the paired gating question is 0 or NA and the bother score is not
missing, the paired bother score is set to NA before computing the count.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_y_pps__bother__yes_count(data) |> select( any_of(c("mh_y_pps__bother__yes_count", vars_mh_y_pps__bother)) ) ## End(Not run)## Not run: compute_mh_y_pps__bother__yes_count(data) |> select( any_of(c("mh_y_pps__bother__yes_count", vars_mh_y_pps__bother)) ) ## End(Not run)
Computes the summary score mh_y_pps__dist__curr_score
Prodromal Psychosis Scale [Youth] (Current Distress Score)
For the current wave, if z-score of mh_y_pps__severity_score normalized
across all current participants in the assessment wave is >= 1.96, set the
value to "1"; else set the value to "0". If there is no score for the current
assessment wave,set the value to NA (missing).
Summarized variables:
mh_y_pps__severity_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_pps__dist__curr_score( data, name = "mh_y_pps__dist__curr_score", combine = TRUE )compute_mh_y_pps__dist__curr_score( data, name = "mh_y_pps__dist__curr_score", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_pps__severity_score()
Computes the summary score mh_y_pps__dist__pers_score
Prodromal Psychosis Scale [Youth] (Persistent Distress Score)
For the last 3 consecutive waves (this wave, prior annual wave, and the wave
before that), if 2 or more waves have a mh_y_pps__dist__curr_score of "1",
then score is "1", else "0";
if more than 1 NA values in the last 3 waves, then score is NA.
The persistent flag is derived from a padded annual timeline per participant.
Missing annual visits between observed sessions are treated as NA,
so each observed session evaluates the current wave plus the two
immediately preceding annual slots, even if data were not collected for
one of those visits.
The special case where both ses-00A and ses-01A meet the threshold (1)
is also treated as persistent at ses-01A.
Summarized variables:
mh_y_pps__dist__curr_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_pps__dist__pers_score( data, name = "mh_y_pps__dist__pers_score", combine = TRUE )compute_mh_y_pps__dist__pers_score( data, name = "mh_y_pps__dist__pers_score", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_pps__dist__curr_score()
Computes the summary score mh_y_pps__severity_mean
Prodromal Psychosis Scale [Youth] (Severity Score): Mean
Summarized variables:
mh_y_pps_001
mh_y_pps_002
mh_y_pps_003
mh_y_pps_004
mh_y_pps_005
mh_y_pps_006
mh_y_pps_007
mh_y_pps_008
mh_y_pps_009
mh_y_pps_010
mh_y_pps_011
mh_y_pps_012
mh_y_pps_013
mh_y_pps_014
mh_y_pps_015
mh_y_pps_016
mh_y_pps_017
mh_y_pps_018
mh_y_pps_019
mh_y_pps_020
mh_y_pps_021
mh_y_pps__severity_001
mh_y_pps__severity_002
mh_y_pps__severity_003
mh_y_pps__severity_004
mh_y_pps__severity_005
mh_y_pps__severity_006
mh_y_pps__severity_007
mh_y_pps__severity_008
mh_y_pps__severity_009
mh_y_pps__severity_010
mh_y_pps__severity_011
mh_y_pps__severity_012
mh_y_pps__severity_013
mh_y_pps__severity_014
mh_y_pps__severity_015
mh_y_pps__severity_016
mh_y_pps__severity_017
mh_y_pps__severity_018
mh_y_pps__severity_019
mh_y_pps__severity_020
mh_y_pps__severity_021
Excluded values: none
Validation criterion: none of 21 items missing
compute_mh_y_pps__severity_mean( data, name = "mh_y_pps__severity_mean", max_na = 0, combine = TRUE )compute_mh_y_pps__severity_mean( data, name = "mh_y_pps__severity_mean", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
The mean severity score is calculated by dividing the total severity
score by the number of mh_y_pps__bother__yes_count. If any of the
two values is missing, the mean severity score is set to NA.
tbl. The input data frame with the summary score appended as a new column.
compute_mh_y_pps__bother__yes_count()
## Not run: compute_mh_y_pps__severity_mean(data) |> select( any_of(c("mh_y_pps__severity_mean", vars_mh_y_pps__severity)) ) ## End(Not run)## Not run: compute_mh_y_pps__severity_mean(data) |> select( any_of(c("mh_y_pps__severity_mean", vars_mh_y_pps__severity)) ) ## End(Not run)
Computes the summary score mh_y_pps__severity_score
Prodromal Psychosis Scale [Youth] (Severity Score)
Summarized variables:
mh_y_pps__severity_001
mh_y_pps__severity_002
mh_y_pps__severity_003
mh_y_pps__severity_004
mh_y_pps__severity_005
mh_y_pps__severity_006
mh_y_pps__severity_007
mh_y_pps__severity_008
mh_y_pps__severity_009
mh_y_pps__severity_010
mh_y_pps__severity_011
mh_y_pps__severity_012
mh_y_pps__severity_013
mh_y_pps__severity_014
mh_y_pps__severity_015
mh_y_pps__severity_016
mh_y_pps__severity_017
mh_y_pps__severity_018
mh_y_pps__severity_019
mh_y_pps__severity_020
mh_y_pps__severity_021
Excluded values: none
Validation criterion: none of 21 items missing
compute_mh_y_pps__severity_score( data, name = "mh_y_pps__severity_score", max_na = 0, combine = TRUE )compute_mh_y_pps__severity_score( data, name = "mh_y_pps__severity_score", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
combine |
logical. If |
The severity score is calculated by summing the severity scores for each
question and adding the number of mh_y_pps__bother__yes_count to the
total.
However, if the mh_y_pps__severity_nm score is greater than max_na,
the severity score is set to NA.
There is also a sanity check for the gating question of PPS
base/bother score. If the paired base/bother question is 0 or NA
and the severity score is not missing, the paired severity score is set
to NA before computing the score.
tbl. see combine.
compute_mh_y_pps__bother__yes_count()
## Not run: compute_mh_y_pps__severity_score(data) |> select( any_of(c("mh_y_pps__severity_score", vars_mh_y_pps__severity)) ) |> View() ## End(Not run)## Not run: compute_mh_y_pps__severity_score(data) |> select( any_of(c("mh_y_pps__severity_score", vars_mh_y_pps__severity)) ) |> View() ## End(Not run)
This super function computes all scores in PPS using all the default arguments.
compute_mh_y_pps_all(data)compute_mh_y_pps_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
Make sure the data is the full set of all variables from PPS
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_pps_all(data) ## End(Not run)## Not run: compute_mh_y_pps_all(data) ## End(Not run)
Computes the summary score mh_y_pps_nm
Prodromal Psychosis Scale [Youth] (number of responses): Number
missing
Summarized variables:
mh_y_pps_001
mh_y_pps_002
mh_y_pps_003
mh_y_pps_004
mh_y_pps_005
mh_y_pps_006
mh_y_pps_007
mh_y_pps_008
mh_y_pps_009
mh_y_pps_010
mh_y_pps_011
mh_y_pps_012
mh_y_pps_013
mh_y_pps_014
mh_y_pps_015
mh_y_pps_016
mh_y_pps_017
mh_y_pps_018
mh_y_pps_019
mh_y_pps_020
mh_y_pps_021
compute_mh_y_pps_nm(data, name = "mh_y_pps_nm", combine = TRUE)compute_mh_y_pps_nm(data, name = "mh_y_pps_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_y_pps_nm(data) |> select( any_of(c("mh_y_pps_nm", vars_mh_y_pps_count)) ) ## End(Not run)## Not run: compute_mh_y_pps_nm(data) |> select( any_of(c("mh_y_pps_nm", vars_mh_y_pps_count)) ) ## End(Not run)
Computes the summary score mh_y_ppsss__dist__curr_count
Prodromal Psychosis Scale [Youth] (Current Distress Count):
Number of times criteria met.
This function creates a static variable from longitudinal data.
Summarized variables:
mh_y_pps__dist__curr_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_ppsss__dist__curr_count( data, name = "mh_y_ppsss__dist__curr_count" )compute_mh_y_ppsss__dist__curr_count( data, name = "mh_y_ppsss__dist__curr_count" )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__curr_score()
Static Prodromal Psychosis Scale [Youth] (Current Distress Ever): Indicates if criteria ever met
This function creates a static variable from longitudinal data.
Summarized variables:
mh_y_pps__dist__curr_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_ppsss__dist__curr_ever(data, name = "mh_y_ppsss__dist__curr_ever")compute_mh_y_ppsss__dist__curr_ever(data, name = "mh_y_ppsss__dist__curr_ever")
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__curr_score()
Static Prodromal Psychosis Scale [Youth] (First Current Distress): Session when criteria first met
This function creates a static variable from longitudinal data.
Summarized variables:
mh_y_pps__dist__curr_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_ppsss__dist__curr_first( data, name = "mh_y_ppsss__dist__curr_first" )compute_mh_y_ppsss__dist__curr_first( data, name = "mh_y_ppsss__dist__curr_first" )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__curr_score()
Computes the summary score mh_y_ppsss__dist__pers_count
Prodromal Psychosis Scale [Youth] (Persistent Distress Count):
Number of times criteria met
This function creates a static variable from longitudinal data.
Summarized variables:
mh_y_pps__dist__pers_score (intermediate score)
Excluded values: none
Validation criterion: none
compute_mh_y_ppsss__dist__pers_count( data, name = "mh_y_ppsss__dist__pers_count" )compute_mh_y_ppsss__dist__pers_count( data, name = "mh_y_ppsss__dist__pers_count" )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__pers_score()
Static Prodromal Psychosis Scale [Youth] (Persistent Distress Ever): Indicates if criteria ever met
Summarized variables:
mh_y_pps__dist__pers_score (intermediate score)
Excluded values: none
Validation criterion: none
This function creates a static variable from longitudinal data.
compute_mh_y_ppsss__dist__pers_ever(data, name = "mh_y_ppsss__dist__pers_ever")compute_mh_y_ppsss__dist__pers_ever(data, name = "mh_y_ppsss__dist__pers_ever")
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__pers_score()
Static Prodromal Psychosis Scale [Youth] (First Persistent Distress): Session when criteria first met
Summarized variables:
mh_y_pps__dist__pers_score (intermediate score)
Excluded values: none
Validation criterion: none
This function creates a static variable from longitudinal data.
compute_mh_y_ppsss__dist__pers_first( data, name = "mh_y_ppsss__dist__pers_first" )compute_mh_y_ppsss__dist__pers_first( data, name = "mh_y_ppsss__dist__pers_first" )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
a tibble of the participant_id column and the new static column
compute_mh_y_pps__dist__pers_score()
A single function to compute all scores in the above domain using default arguments.
compute_mh_y_ppsss_all(data)compute_mh_y_ppsss_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
a tibble of the participant_id column and the new static columns
This function computes all summary scores for the mh_y_sup table. Make sure to have all necessary columns in the data frame.
compute_mh_y_sup_all(data)compute_mh_y_sup_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_sup_all(data) ## End(Not run)## Not run: compute_mh_y_sup_all(data) ## End(Not run)
Computes the summary score mh_y_sup_sum
7-Up Mania Inventory [Youth]: Sum
Summarized variables:
mh_y_sup_001
mh_y_sup_002
mh_y_sup_003
mh_y_sup_004
mh_y_sup_005
mh_y_sup_006
mh_y_sup_007
Excluded values: none
Validation criterion: none of 7 items missing
compute_mh_y_sup_sum( data, name = "mh_y_sup_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_sup_sum( data, name = "mh_y_sup_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_sup_sum(data) |> select( any_of(c("mh_y_sup_sum", vars_mh_y_sup)) ) ## End(Not run)## Not run: compute_mh_y_sup_sum(data) |> select( any_of(c("mh_y_sup_sum", vars_mh_y_sup)) ) ## End(Not run)
Computes the summary score mh_y_upps__nurg_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative
Urgency): Sum
Summarized variables:
mh_y_upps__nurg_001
mh_y_upps__nurg_002
mh_y_upps__nurg_003
mh_y_upps__nurg_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_upps__nurg_sum( data, name = "mh_y_upps__nurg_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_upps__nurg_sum( data, name = "mh_y_upps__nurg_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_upps__nurg_sum(data) |> select( any_of(c("mh_y_upps__nurg_sum", vars_mh_y_upps__nurg)) ) ## End(Not run)## Not run: compute_mh_y_upps__nurg_sum(data) |> select( any_of(c("mh_y_upps__nurg_sum", vars_mh_y_upps__nurg)) ) ## End(Not run)
Computes the summary score mh_y_upps__pers_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Perseverance (GSSF)): Sum
Summarized variables:
mh_y_upps__pers_001
mh_y_upps__pers_002
mh_y_upps__pers_003
mh_y_upps__pers_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_upps__pers_sum( data, name = "mh_y_upps__pers_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_upps__pers_sum( data, name = "mh_y_upps__pers_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_upps__pers_sum(data) |> select( any_of(c("mh_y_upps__pers_sum", vars_mh_y_upps__pers)) ) ## End(Not run)## Not run: compute_mh_y_upps__pers_sum(data) |> select( any_of(c("mh_y_upps__pers_sum", vars_mh_y_upps__pers)) ) ## End(Not run)
Computes the summary score mh_y_upps__plan_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Planning): Sum
Summarized variables:
mh_y_upps__plan_001
mh_y_upps__plan_002
mh_y_upps__plan_003
mh_y_upps__plan_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_upps__plan_sum( data, name = "mh_y_upps__plan_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_upps__plan_sum( data, name = "mh_y_upps__plan_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_upps__plan_sum(data) |> select( any_of(c("mh_y_upps__plan_sum", vars_mh_y_upps__plan)) ) ## End(Not run)## Not run: compute_mh_y_upps__plan_sum(data) |> select( any_of(c("mh_y_upps__plan_sum", vars_mh_y_upps__plan)) ) ## End(Not run)
Computes the summary score mh_y_upps__purg_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive
Urgency): Sum
Summarized variables:
mh_y_upps__purg_001
mh_y_upps__purg_002
mh_y_upps__purg_003
mh_y_upps__purg_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_upps__purg_sum( data, name = "mh_y_upps__purg_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_upps__purg_sum( data, name = "mh_y_upps__purg_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_upps__purg_sum(data) |> select( any_of(c("mh_y_upps__purg_sum", vars_mh_y_upps__purg)) ) ## End(Not run)## Not run: compute_mh_y_upps__purg_sum(data) |> select( any_of(c("mh_y_upps__purg_sum", vars_mh_y_upps__purg)) ) ## End(Not run)
Computes the summary score mh_y_upps__sens_sum
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation
Seeking): Sum
Summarized variables:
mh_y_upps__sens_001
mh_y_upps__sens_002
mh_y_upps__sens_003
mh_y_upps__sens_004
Excluded values: none
Validation criterion: none of 4 items missing
compute_mh_y_upps__sens_sum( data, name = "mh_y_upps__sens_sum", max_na = 0, exclude = NULL, combine = TRUE )compute_mh_y_upps__sens_sum( data, name = "mh_y_upps__sens_sum", max_na = 0, exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_upps__sens_sum(data) |> select( any_of(c("mh_y_upps__sens_sum", vars_mh_y_upps__sens)) ) ## End(Not run)## Not run: compute_mh_y_upps__sens_sum(data) |> select( any_of(c("mh_y_upps__sens_sum", vars_mh_y_upps__sens)) ) ## End(Not run)
This function computes all summary scores for the mh_y_upps table. Make sure to have all necessary columns in the data frame.
compute_mh_y_upps_all(data)compute_mh_y_upps_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_upps_all(data) ## End(Not run)## Not run: compute_mh_y_upps_all(data) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__adhd_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Sum
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 0 of 7 items missing
compute_mh_y_ysr__dsm__adhd_sum( data, name = "mh_y_ysr__dsm__adhd_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__adhd_sum( data, name = "mh_y_ysr__dsm__adhd_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__adhd_nm()
## Not run: compute_mh_y_ysr__dsm__adhd_sum(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_sum", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__adhd_sum(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_sum", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__adhd_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): T-score
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 1 of 7 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__adhd_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__adhd_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__adhd_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__adhd_nm()
## Not run: compute_mh_y_ysr__dsm__adhd_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_tscore", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__adhd_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_tscore", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__anx_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
Sum
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
compute_mh_y_ysr__dsm__anx_sum( data, name = "mh_y_ysr__dsm__anx_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__anx_sum( data, name = "mh_y_ysr__dsm__anx_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__anx_nm()
## Not run: compute_mh_y_ysr__dsm__anx_sum(data) |> select( any_of(c("mh_y_ysr__dsm__anx_sum", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__anx_sum(data) |> select( any_of(c("mh_y_ysr__dsm__anx_sum", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__anx_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
T-score
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__anx_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__anx_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__anx_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__anx_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__anx_nm()
## Not run: compute_mh_y_ysr__dsm__anx_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__anx_tscore", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__anx_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__anx_tscore", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__cond_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
Sum
Summarized variables:
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
Excluded values:
777
999
Validation criterion: maximally 3 of 15 items missing
compute_mh_y_ysr__dsm__cond_sum( data, name = "mh_y_ysr__dsm__cond_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__cond_sum( data, name = "mh_y_ysr__dsm__cond_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__cond_nm()
## Not run: compute_mh_y_ysr__dsm__cond_sum(data) |> select( any_of(c("mh_y_ysr__dsm__cond_sum", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__cond_sum(data) |> select( any_of(c("mh_y_ysr__dsm__cond_sum", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__cond_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
T-score
Summarized variables:
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
Excluded values:
777
999
Validation criterion: maximally 3 of 15 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__cond_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__cond_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__cond_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__cond_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__cond_nm()
## Not run: compute_mh_y_ysr__dsm__cond_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__cond_tscore", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__cond_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__cond_tscore", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__dep_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): Sum
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
compute_mh_y_ysr__dsm__dep_sum( data, name = "mh_y_ysr__dsm__dep_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__dep_sum( data, name = "mh_y_ysr__dsm__dep_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__dep_nm()
## Not run: compute_mh_y_ysr__dsm__dep_sum(data) |> select( any_of(c("mh_y_ysr__dsm__dep_sum", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__dep_sum(data) |> select( any_of(c("mh_y_ysr__dsm__dep_sum", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__dep_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): T-score
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__dep_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__dep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__dep_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__dep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__dep_nm()
## Not run: compute_mh_y_ysr__dsm__dep_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__dep_tscore", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__dep_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__dep_tscore", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__opp_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): Sum
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
Excluded values:
777
999
Validation criterion: maximally 1 of 5 items missing
compute_mh_y_ysr__dsm__opp_sum( data, name = "mh_y_ysr__dsm__opp_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__opp_sum( data, name = "mh_y_ysr__dsm__opp_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__opp_nm()
## Not run: compute_mh_y_ysr__dsm__opp_sum(data) |> select( any_of(c("mh_y_ysr__dsm__opp_sum", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__opp_sum(data) |> select( any_of(c("mh_y_ysr__dsm__opp_sum", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__opp_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): T-score
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
Excluded values:
777
999
Validation criterion: maximally 1 of 5 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__opp_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__opp_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__opp_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__opp_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__opp_nm()
## Not run: compute_mh_y_ysr__dsm__opp_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__opp_tscore", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__opp_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__opp_tscore", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__somat_sum
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
Sum
Summarized variables:
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 1 of 7 items missing
compute_mh_y_ysr__dsm__somat_sum( data, name = "mh_y_ysr__dsm__somat_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__somat_sum( data, name = "mh_y_ysr__dsm__somat_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__somat_nm()
## Not run: compute_mh_y_ysr__dsm__somat_sum(data) |> select( any_of(c("mh_y_ysr__dsm__somat_sum", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__somat_sum(data) |> select( any_of(c("mh_y_ysr__dsm__somat_sum", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__somat_tscore
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
T-score
Summarized variables:
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 1 of 7 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__dsm__somat_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__somat_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__dsm__somat_tscore( data, data_norm = NULL, name = "mh_y_ysr__dsm__somat_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__dsm__somat_nm()
## Not run: compute_mh_y_ysr__dsm__somat_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__somat_tscore", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__somat_tscore(data) |> select( any_of(c("mh_y_ysr__dsm__somat_tscore", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_y_ysr__pos_sum
Youth Self Report [Youth] (Positive): Sum
Summarized variables:
mh_y_ysr__pos_001
mh_y_ysr__pos_002
mh_y_ysr__pos_003
mh_y_ysr__pos_004
mh_y_ysr__pos_005
mh_y_ysr__pos_006
mh_y_ysr__pos_007
mh_y_ysr__pos_008
mh_y_ysr__pos_009
mh_y_ysr__pos_010
mh_y_ysr__pos_011
mh_y_ysr__pos_012
mh_y_ysr__pos_013
mh_y_ysr__pos_014
Excluded values:
777
999
Validation criterion: maximally 2 of 14 items missing
compute_mh_y_ysr__pos_sum( data, name = "mh_y_ysr__pos_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__pos_sum( data, name = "mh_y_ysr__pos_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_ysr__pos_sum(data) |> select( any_of(c("mh_y_ysr__pos_sum", vars_mh_y_ysr__pos)) ) ## End(Not run)## Not run: compute_mh_y_ysr__pos_sum(data) |> select( any_of(c("mh_y_ysr__pos_sum", vars_mh_y_ysr__pos)) ) ## End(Not run)
Computes the summary score mh_y_ysr__pos_tscore
Youth Self Report [Youth] (Positive): T-score
Summarized variables:
mh_y_ysr__pos_001
mh_y_ysr__pos_002
mh_y_ysr__pos_003
mh_y_ysr__pos_004
mh_y_ysr__pos_005
mh_y_ysr__pos_006
mh_y_ysr__pos_007
mh_y_ysr__pos_008
mh_y_ysr__pos_009
mh_y_ysr__pos_010
mh_y_ysr__pos_011
mh_y_ysr__pos_012
mh_y_ysr__pos_013
mh_y_ysr__pos_014
Excluded values:
777
999
Validation criterion: maximally 2 of 14 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__pos_tscore( data, data_norm = NULL, name = "mh_y_ysr__pos_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__pos_tscore( data, data_norm = NULL, name = "mh_y_ysr__pos_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_ysr__pos_tscore(data) |> select( any_of(c("mh_y_ysr__pos_tscore", vars_mh_y_ysr__pos)) ) ## End(Not run)## Not run: compute_mh_y_ysr__pos_tscore(data) |> select( any_of(c("mh_y_ysr__pos_tscore", vars_mh_y_ysr__pos)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__aggr_sum
Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior): Sum
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 3 of 17 items missing
compute_mh_y_ysr__synd__aggr_sum( data, name = "mh_y_ysr__synd__aggr_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__aggr_sum( data, name = "mh_y_ysr__synd__aggr_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__aggr_nm()
## Not run: compute_mh_y_ysr__synd__aggr_sum(data) |> select( any_of(c("mh_y_ysr__synd__aggr_sum", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__aggr_sum(data) |> select( any_of(c("mh_y_ysr__synd__aggr_sum", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__aggr_tscore
Youth Self Report [Youth] (Syndrome Scale - Aggressive): T-score
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 3 of 17 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__aggr_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__aggr_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__aggr_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__aggr_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__aggr_nm()
## Not run: compute_mh_y_ysr__synd__aggr_tscore(data) |> select( any_of(c("mh_y_ysr__synd__aggr_tscore", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__aggr_tscore(data) |> select( any_of(c("mh_y_ysr__synd__aggr_tscore", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__anxdep_sum
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Sum
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
Validation criterion: maximally 2 of 12 items missing
compute_mh_y_ysr__synd__anxdep_sum( data, name = "mh_y_ysr__synd__anxdep_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__anxdep_sum( data, name = "mh_y_ysr__synd__anxdep_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__anxdep_nm()
## Not run: compute_mh_y_ysr__synd__anxdep_sum(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_sum", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__anxdep_sum(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_sum", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__anxdep_tscore
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed):
T-score
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
Validation criterion: maximally 2 of 12 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__anxdep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__anxdep_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__anxdep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__anxdep_nm()
## Not run: compute_mh_y_ysr__synd__anxdep_tscore(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_tscore", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__anxdep_tscore(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_tscore", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__attn_sum
Youth Self Report [Youth] (Syndrome Scale - Attention problems): Sum
Summarized variables:
mh_y_ysr__attn_001
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn_004
mh_y_ysr__attn__adhd_005
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
compute_mh_y_ysr__synd__attn_sum( data, name = "mh_y_ysr__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__attn_sum( data, name = "mh_y_ysr__synd__attn_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__attn_nm()
## Not run: compute_mh_y_ysr__synd__attn_sum(data) |> select( any_of(c("mh_y_ysr__synd__attn_sum", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__attn_sum(data) |> select( any_of(c("mh_y_ysr__synd__attn_sum", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__attn_tscore
Youth Self Report [Youth] (Syndrome Scale - Attention problems):
T-score
Summarized variables:
mh_y_ysr__attn_001
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn_004
mh_y_ysr__attn__adhd_005
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__attn_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__attn_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__attn_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__attn_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__attn_nm()
## Not run: compute_mh_y_ysr__synd__attn_tscore(data) |> select( any_of(c("mh_y_ysr__synd__attn_tscore", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__attn_tscore(data) |> select( any_of(c("mh_y_ysr__synd__attn_tscore", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__ext_sum
Youth Self Report [Youth] (Syndrome Scale - External): Sum
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 6 of 32 items missing
compute_mh_y_ysr__synd__ext_sum( data, name = "mh_y_ysr__synd__ext_sum", max_na = 6, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__ext_sum( data, name = "mh_y_ysr__synd__ext_sum", max_na = 6, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__ext_nm()
## Not run: compute_mh_y_ysr__synd__ext_sum(data) |> select( any_of(c("mh_y_ysr__synd__ext_sum", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__ext_sum(data) |> select( any_of(c("mh_y_ysr__synd__ext_sum", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__ext_tscore
Youth Self Report [Youth] (Syndrome Scale - External): T-score
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 6 of 32 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__ext_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__ext_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 6, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__ext_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__ext_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 6, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__ext_nm()
## Not run: compute_mh_y_ysr__synd__ext_tscore(data) |> select( any_of(c("mh_y_ysr__synd__ext_tscore", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__ext_tscore(data) |> select( any_of(c("mh_y_ysr__synd__ext_tscore", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__int_sum
Youth Self Report [Youth] (Syndrome Scale - Internaling): Sum
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 6 of 30 items missing
compute_mh_y_ysr__synd__int_sum( data, name = "mh_y_ysr__synd__int_sum", max_na = 6, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__int_sum( data, name = "mh_y_ysr__synd__int_sum", max_na = 6, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__int_nm()
## Not run: compute_mh_y_ysr__synd__int_sum(data) |> select( any_of(c("mh_y_ysr__synd__int_sum", vars_mh_y_ysr__synd__int)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__int_sum(data) |> select( any_of(c("mh_y_ysr__synd__int_sum", vars_mh_y_ysr__synd__int)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__int_tscore
Youth Self Report [Youth] (Syndrome Scale - Internaling): T-score
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 6 of 30 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__int_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__int_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 6, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__int_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__int_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 6, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__int_nm()
## Not run: compute_mh_y_ysr__synd__int_tscore(data) |> select( any_of(c("mh_y_ysr__synd__int_tscore", vars_mh_y_ysr__synd__int)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__int_tscore(data) |> select( any_of(c("mh_y_ysr__synd__int_tscore", vars_mh_y_ysr__synd__int)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__othpr_sum
Youth Self Report [Youth] (Other problems): Sum
Summarized variables:
mh_y_ysr__othpr_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__othpr_002
mh_y_ysr__othpr_003
mh_y_ysr__othpr_004
mh_y_ysr__othpr_005
mh_y_ysr__othpr_006
mh_y_ysr__othpr__dep_002
mh_y_ysr__othpr__adhd_001
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
compute_mh_y_ysr__synd__othpr_sum( data, name = "mh_y_ysr__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__othpr_sum( data, name = "mh_y_ysr__synd__othpr_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__othpr_nm()
## Not run: compute_mh_y_ysr__synd__othpr_sum(data) |> select( any_of(c("mh_y_ysr__synd__othpr_sum", vars_mh_y_ysr__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__othpr_sum(data) |> select( any_of(c("mh_y_ysr__synd__othpr_sum", vars_mh_y_ysr__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__rule_sum
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
Sum
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
Excluded values:
777
999
Validation criterion: maximally 3 of 15 items missing
compute_mh_y_ysr__synd__rule_sum( data, name = "mh_y_ysr__synd__rule_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__rule_sum( data, name = "mh_y_ysr__synd__rule_sum", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__rule_nm()
## Not run: compute_mh_y_ysr__synd__rule_sum(data) |> select( any_of(c("mh_y_ysr__synd__rule_sum", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__rule_sum(data) |> select( any_of(c("mh_y_ysr__synd__rule_sum", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__rule_tscore
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
T-score
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
Excluded values:
777
999
Validation criterion: maximally 3 of 15 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__rule_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__rule_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__rule_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__rule_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__rule_nm()
## Not run: compute_mh_y_ysr__synd__rule_tscore(data) |> select( any_of(c("mh_y_ysr__synd__rule_tscore", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__rule_tscore(data) |> select( any_of(c("mh_y_ysr__synd__rule_tscore", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__soc_sum
Youth Self Report [Youth] (Syndrome Scale -Social problems): Sum
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
compute_mh_y_ysr__synd__soc_sum( data, name = "mh_y_ysr__synd__soc_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__soc_sum( data, name = "mh_y_ysr__synd__soc_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__soc_nm()
## Not run: compute_mh_y_ysr__synd__soc_sum(data) |> select( any_of(c("mh_y_ysr__synd__soc_sum", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__soc_sum(data) |> select( any_of(c("mh_y_ysr__synd__soc_sum", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__soc_tscore
Youth Self Report [Youth] (Syndrome Scale -Social): T-score
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__soc_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__soc_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__soc_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__soc_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__soc_nm()
## Not run: compute_mh_y_ysr__synd__soc_tscore(data) |> select( any_of(c("mh_y_ysr__synd__soc_tscore", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__soc_tscore(data) |> select( any_of(c("mh_y_ysr__synd__soc_tscore", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__som_sum
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints): Sum
Summarized variables:
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 10 items missing
compute_mh_y_ysr__synd__som_sum( data, name = "mh_y_ysr__synd__som_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__som_sum( data, name = "mh_y_ysr__synd__som_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__som_nm()
## Not run: compute_mh_y_ysr__synd__som_sum(data) |> select( any_of(c("mh_y_ysr__synd__som_sum", vars_mh_y_ysr__synd__som)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__som_sum(data) |> select( any_of(c("mh_y_ysr__synd__som_sum", vars_mh_y_ysr__synd__som)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__som_tscore
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints):
T-score
Summarized variables:
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
Validation criterion: maximally 2 of 10 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__som_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__som_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__som_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__som_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__som_nm()
## Not run: compute_mh_y_ysr__synd__som_tscore(data) |> select( any_of(c("mh_y_ysr__synd__som_tscore", vars_mh_y_ysr__synd__som)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__som_tscore(data) |> select( any_of(c("mh_y_ysr__synd__som_tscore", vars_mh_y_ysr__synd__som)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__tho_sum
Youth Self Report [Youth] (Syndrome Scale - Thought problems): Sum
Summarized variables:
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho__dep_002
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
mh_y_ysr__tho__dep_003
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
compute_mh_y_ysr__synd__tho_sum( data, name = "mh_y_ysr__synd__tho_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__tho_sum( data, name = "mh_y_ysr__synd__tho_sum", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__tho_nm()
## Not run: compute_mh_y_ysr__synd__tho_sum(data) |> select( any_of(c("mh_y_ysr__synd__tho_sum", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__tho_sum(data) |> select( any_of(c("mh_y_ysr__synd__tho_sum", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__tho_tscore
Youth Self Report [Youth] (Syndrome Scale - Thought problems): T-score
Summarized variables:
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho__dep_002
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
mh_y_ysr__tho__dep_003
Excluded values:
777
999
Validation criterion: maximally 2 of 11 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__tho_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__tho_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__tho_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__tho_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__tho_nm()
## Not run: compute_mh_y_ysr__synd__tho_tscore(data) |> select( any_of(c("mh_y_ysr__synd__tho_tscore", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__tho_tscore(data) |> select( any_of(c("mh_y_ysr__synd__tho_tscore", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__wthdep_sum
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed): Sum
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
Excluded values:
777
999
Validation criterion: maximally 1 of 8 items missing
compute_mh_y_ysr__synd__wthdep_sum( data, name = "mh_y_ysr__synd__wthdep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__wthdep_sum( data, name = "mh_y_ysr__synd__wthdep_sum", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__wthdep_nm()
## Not run: compute_mh_y_ysr__synd__wthdep_sum(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_sum", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__wthdep_sum(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_sum", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__wthdep_tscore
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed):
T-score
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
Excluded values:
777
999
Validation criterion: maximally 1 of 8 items missing
or mh_y_ysr__dsm__adhd_nm <= 5
compute_mh_y_ysr__synd__wthdep_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__wthdep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr__synd__wthdep_tscore( data, data_norm = NULL, name = "mh_y_ysr__synd__wthdep_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
compute_mh_y_ysr__synd__wthdep_nm()
## Not run: compute_mh_y_ysr__synd__wthdep_tscore(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_tscore", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__wthdep_tscore(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_tscore", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)
This function computes all summary scores for the mh_y_ysr form. Make sure to have all necessary columns in the data frame.
compute_mh_y_ysr_all(data)compute_mh_y_ysr_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_mh_y_ysr_all(data) ## End(Not run)## Not run: compute_mh_y_ysr_all(data) ## End(Not run)
Computes the summary score mh_y_ysr_sum
Youth Self Report [Youth]: Sum
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr_003
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__attn_001
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn_004
mh_y_ysr__rule_001
mh_y_ysr__rule_002
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule_005
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep_005
mh_y_ysr__som_001
mh_y_ysr__othpr_001
mh_y_ysr__othpr_002
mh_y_ysr__othpr_003
mh_y_ysr__othpr_004
mh_y_ysr__othpr_005
mh_y_ysr__othpr_006
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
Excluded values:
777
999
Validation criterion: maximally 5 of 102 items missing
compute_mh_y_ysr_sum( data, name = "mh_y_ysr_sum", max_na = 5, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr_sum( data, name = "mh_y_ysr_sum", max_na = 5, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_ysr_sum(data) |> select( any_of(c("mh_y_ysr_sum", vars_mh_y_ysr)) ) ## End(Not run)## Not run: compute_mh_y_ysr_sum(data) |> select( any_of(c("mh_y_ysr_sum", vars_mh_y_ysr)) ) ## End(Not run)
Computes the summary score mh_y_ysr_tscore
Youth Self Report [Youth]: T-score
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr_003
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__attn_001
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn_004
mh_y_ysr__rule_001
mh_y_ysr__rule_002
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule_005
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep_005
mh_y_ysr__som_001
mh_y_ysr__othpr_001
mh_y_ysr__othpr_002
mh_y_ysr__othpr_003
mh_y_ysr__othpr_004
mh_y_ysr__othpr_005
mh_y_ysr__othpr_006
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
Excluded values:
777
999
Validation criterion: maximally 5 of 102 items missing
compute_mh_y_ysr_tscore( data, data_norm = NULL, name = "mh_y_ysr_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 5, exclude = c("777", "999"), combine = TRUE )compute_mh_y_ysr_tscore( data, data_norm = NULL, name = "mh_y_ysr_tscore", col_age = "mh_y_ysr_age", col_sex = "ab_g_stc__cohort_sex", max_na = 5, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the norm (T-score) values.
see |
name |
character. Name of the summary score column. |
col_age |
character, name of the age column. see |
col_sex |
character, name of the sex column. see |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
tbl. see combine.
## Not run: compute_mh_y_ysr_tscore(data) |> select( any_of(c("mh_y_ysr_tscore", vars_mh_y_ysr)) ) ## End(Not run)## Not run: compute_mh_y_ysr_tscore(data) |> select( any_of(c("mh_y_ysr_tscore", vars_mh_y_ysr)) ) ## End(Not run)
Computes the summary score nc_p_bdefs__sympt_count
Barkley Deficits in Executive Functioning Scale [Parent] (EF Symptom
Count, number of answers of 3 or 4): Count
Summarized variables:
nc_p_bdefs_001
nc_p_bdefs_002
nc_p_bdefs_003
nc_p_bdefs_004
nc_p_bdefs_005
nc_p_bdefs_006
nc_p_bdefs_007
nc_p_bdefs_008
nc_p_bdefs_009
nc_p_bdefs_010
nc_p_bdefs_011
nc_p_bdefs_012
nc_p_bdefs_013
nc_p_bdefs_014
nc_p_bdefs_015
nc_p_bdefs_016
nc_p_bdefs_017
nc_p_bdefs_018
nc_p_bdefs_019
nc_p_bdefs_020
compute_nc_p_bdefs__sympt_count( data, name = "nc_p_bdefs__sympt_count", max_na = 0, combine = TRUE )compute_nc_p_bdefs__sympt_count( data, name = "nc_p_bdefs__sympt_count", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_nc_p_bdefs__sympt_count(data) |> select( data, all_of(c("nc_p_bdefs__sympt_count", vars_nc_p_bdefs)) ) ## End(Not run)## Not run: compute_nc_p_bdefs__sympt_count(data) |> select( data, all_of(c("nc_p_bdefs__sympt_count", vars_nc_p_bdefs)) ) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_nc_p_bdefs_all(data)compute_nc_p_bdefs_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_nc_p_bdefs_all(data) ## End(Not run)## Not run: compute_nc_p_bdefs_all(data) ## End(Not run)
Computes the summary score nc_p_bdefs_nm
Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary
Score): Number missing
Summarized variables:
nc_p_bdefs_001
nc_p_bdefs_002
nc_p_bdefs_003
nc_p_bdefs_004
nc_p_bdefs_005
nc_p_bdefs_006
nc_p_bdefs_007
nc_p_bdefs_008
nc_p_bdefs_009
nc_p_bdefs_010
nc_p_bdefs_011
nc_p_bdefs_012
nc_p_bdefs_013
nc_p_bdefs_014
nc_p_bdefs_015
nc_p_bdefs_016
nc_p_bdefs_017
nc_p_bdefs_018
nc_p_bdefs_019
nc_p_bdefs_020
compute_nc_p_bdefs_nm(data, name = "nc_p_bdefs_nm", combine = TRUE)compute_nc_p_bdefs_nm(data, name = "nc_p_bdefs_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_nc_p_bdefs_nm(data) |> select( data, all_of(c("nc_p_bdefs_nm", vars_nc_p_bdefs)) ) ## End(Not run)## Not run: compute_nc_p_bdefs_nm(data) |> select( data, all_of(c("nc_p_bdefs_nm", vars_nc_p_bdefs)) ) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_nc_y_ehis_all(data)compute_nc_y_ehis_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_nc_y_ehis_all(data) ## End(Not run)## Not run: compute_nc_y_ehis_all(data) ## End(Not run)
Computes the summary score nc_y_ehis_nm
Edinburgh Handedness Inventory [Youth]: Number missing
Summarized variables:
nc_y_ehis_001
nc_y_ehis_002
nc_y_ehis_003
nc_y_ehis_004
compute_nc_y_ehis_nm(data, name = "nc_y_ehis_nm", combine = TRUE)compute_nc_y_ehis_nm(data, name = "nc_y_ehis_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_nc_y_ehis_nm(data) |> select( data, all_of(c("nc_y_ehis_nm", vars_nc_y_ehis)) ) ## End(Not run)## Not run: compute_nc_y_ehis_nm(data) |> select( data, all_of(c("nc_y_ehis_nm", vars_nc_y_ehis)) ) ## End(Not run)
Computes the summary score nt_p_yst__pmum_nm
Youth Screen Time [Parent] (Problematic Media Use): Number missing
Summarized variables:
nt_p_yst__pmum_001
nt_p_yst__pmum_002
nt_p_yst__pmum_003
nt_p_yst__pmum_004
nt_p_yst__pmum_005
nt_p_yst__pmum_006
nt_p_yst__pmum_007
nt_p_yst__pmum_008
nt_p_yst__pmum_009
Excluded values:
777
999
compute_nt_p_yst__pmum_nm(data, name = "nt_p_yst__pmum_nm", combine = TRUE)compute_nt_p_yst__pmum_nm(data, name = "nt_p_yst__pmum_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_p_yst__screen__wkdy_nm
Youth Screen Time [Parent] (Weekday): Number missing
Summarized variables:
nt_p_yst__wkdy__hr_001
nt_p_yst__wkdy__min_001
nt_p_yst__wkdy__min_001__v01
Excluded values:
777
999
compute_nt_p_yst__screen__wkdy_nm( data, name = "nt_p_yst__screen__wkdy_nm", combine = TRUE )compute_nt_p_yst__screen__wkdy_nm( data, name = "nt_p_yst__screen__wkdy_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_p_yst__screen__wknd_nm
Youth Screen Time [Parent] (Weekend): Number missing
Summarized variables:
nt_p_yst__wknd__hr_001
nt_p_yst__wknd__min_001
nt_p_yst__wknd__min_001__v01
Excluded values:
777
999
compute_nt_p_yst__screen__wknd_nm( data, name = "nt_p_yst__screen__wknd_nm", combine = TRUE )compute_nt_p_yst__screen__wknd_nm( data, name = "nt_p_yst__screen__wknd_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the nt_p_yst form. Make sure to have all necessary columns in the data frame.
compute_nt_p_yst_all(data)compute_nt_p_yst_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_nt_p_yst_all(data) ## End(Not run)## Not run: compute_nt_p_yst_all(data) ## End(Not run)
Computes the summary score nt_y_stq__screen__wkdy_nm
Screen Time [Youth] (Weekday): Number missing
Summarized variables:
nt_y_stq__screen__wkdy_001
nt_y_stq__screen__wkdy_002
nt_y_stq__screen__wkdy_003
nt_y_stq__screen__wkdy_004
nt_y_stq__screen__wkdy_005
nt_y_stq__screen__wkdy_006
nt_y_stq__screen__wkdy__hr_001
nt_y_stq__screen__wkdy__min_001
nt_y_stq__screen__wkdy__hr_001__v01
nt_y_stq__screen__wkdy__min_001__v01
nt_y_stq__screen__wkdy__hr_002
nt_y_stq__screen__wkdy__min_002
nt_y_stq__screen__wkdy__hr_003
nt_y_stq__screen__wkdy__min_003
nt_y_stq__screen__wkdy__hr_004
nt_y_stq__screen__wkdy__min_004
nt_y_stq__screen__wkdy__hr_005
nt_y_stq__screen__wkdy__min_005
nt_y_stq__screen__wkdy__hr_006
nt_y_stq__screen__wkdy__min_006
nt_y_stq__screen__wkdy__hr_007
nt_y_stq__screen__wkdy__min_007
nt_y_stq__screen__wkdy__hr_008
nt_y_stq__screen__wkdy__min_008
nt_y_stq__screen__wkdy__hr_009
nt_y_stq__screen__wkdy__min_009
Excluded values:
777
999
compute_nt_y_stq__screen__wkdy_nm( data, name = "nt_y_stq__screen__wkdy_nm", combine = TRUE )compute_nt_y_stq__screen__wkdy_nm( data, name = "nt_y_stq__screen__wkdy_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_y_stq__screen__wknd_nm
Screen Time [Youth] (Weekend): Number missing
Summarized variables:
nt_y_stq__screen__wknd_001
nt_y_stq__screen__wknd_002
nt_y_stq__screen__wknd_003
nt_y_stq__screen__wknd_004
nt_y_stq__screen__wknd_005
nt_y_stq__screen__wknd_006
nt_y_stq__screen__wknd__hr_001
nt_y_stq__screen__wknd__min_001
nt_y_stq__screen__wknd__hr_001__v01
nt_y_stq__screen__wknd__min_001__v01
nt_y_stq__screen__wknd__hr_002
nt_y_stq__screen__wknd__min_002
nt_y_stq__screen__wknd__hr_003
nt_y_stq__screen__wknd__min_003
nt_y_stq__screen__wknd__hr_004
nt_y_stq__screen__wknd__min_004
nt_y_stq__screen__wknd__hr_005
nt_y_stq__screen__wknd__min_005
nt_y_stq__screen__wknd__hr_006
nt_y_stq__screen__wknd__min_006
nt_y_stq__screen__wknd__hr_007
nt_y_stq__screen__wknd__min_007
nt_y_stq__screen__wknd__hr_008
nt_y_stq__screen__wknd__min_008
nt_y_stq__screen__wknd__hr_009
nt_y_stq__screen__wknd__min_009
Excluded values:
777
999
compute_nt_y_stq__screen__wknd_nm( data, name = "nt_y_stq__screen__wknd_nm", combine = TRUE )compute_nt_y_stq__screen__wknd_nm( data, name = "nt_y_stq__screen__wknd_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the nt_y_stq form. Make sure to have all necessary columns in the data frame.
compute_nt_y_stq_all(data)compute_nt_y_stq_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_nt_y_stq_all(data) ## End(Not run)## Not run: compute_nt_y_stq_all(data) ## End(Not run)
This function computes all medication category mapping summary scores
based on the provided configuration in rx_config by mapping medication
RxCUI codes to their respective categories that are stored in
ABCDscores::rx_map.
It processes each row in rx_config. One row corresponds to one medication
category mapping score. For each row, it first checks col_summary1. If
col_summary1 has data, that value is used. If col_summary1 is NA, it
falls back to col_summary2.
It then applies col_add filtering only when both conditions are met:
the corresponding flag (use_col_add1 or use_col_add2) is TRUE, and
col_add is provided (not NA).
When filtering is applied, only rows with col_add == "1" are retained;
otherwise, the selected RxCUI is set to NA.
After source selection and optional filtering, it maps the retained RxCUI
codes to their respective
categories using the appropriate mapping data frame from ABCDscores::rx_map
based on the catg specified in rx_config. The resulting category values
are then stored in a new column named as specified in the name column of
rx_config.
Summarized variables: see rx_config for the list of variables.
compute_ph_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_y_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_dhx_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE )compute_ph_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_y_meds_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_dhx_catg_all( data, rx_config = ABCDscores::rx_config, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
rx_config |
tbl, Configuration tibble specifying the medication
category mappings to compute. Default is |
combine |
logical, If |
"This product uses publicly available data from the U.S. National Library of Medicine (NLM), National Institutes of Health, Department of Health and Human Services; NLM is not responsible for the product and does not endorse or recommend this or any other product."
compute_ph_meds_catg_all(): Computes all medication category
mappings across all tables.
compute_ph_p_meds_catg_all(): Computes all medication category
mappings for the ph_p_meds table.
compute_ph_y_meds_catg_all(): Computes all medication category
mappings for the ph_y_meds table.
compute_ph_p_dhx_catg_all(): Computes all medication category
mappings for the ph_p_dhx table.
tbl. see combine parameter.
The medical estimated use values and categories are generated from: Lopez, D. A., Overholtzer, L. N., Rhee, K. E., Buchbinder, N., Ruiz-Orozco, G. E., Steinhilber, S., Tognoli, M., Lopez-Flores, A., & Nagel, B. J. (2025). Classifying and visualizing medication use in the Adolescent Brain Cognitive Development (ABCD) Study. medRxiv.
This function computes all medication estimated use flag summary scores
based on the provided configuration in rx_config_estuse_flags and the
computed medication categories from rx_config.
It first calls compute_ph_meds_catg_all() to obtain the medication category
mappings of all estuse categories. Then, for each row in
rx_config_estuse_flags, it checks if any of the corresponding medication
category mapping scores (from both OTC and RX medications) match the
specified idx category index. If a match is found, it assigns a value of
"1" to indicate estimated use; otherwise, it assigns "0". The resulting
estimated use flags are stored in new columns named as specified in the
name column of rx_config_estuse_flags.
Summarized variables: see rx_config for the list of variables.
compute_ph_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_y_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE )compute_ph_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_p_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE ) compute_ph_y_meds_estuse_flags_all( data, rx_config_estuse_flags = ABCDscores::rx_config_estuse_flags, rx_config = ABCDscores::rx_config, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
rx_config_estuse_flags |
tbl, Configuration tibble specifying the
estimated use flag mappings to compute. Default is
|
rx_config |
tbl, Configuration tibble specifying the medication
category mappings to compute. Default is |
combine |
logical, If |
"This product uses publicly available data from the U.S. National Library of Medicine (NLM), National Institutes of Health, Department of Health and Human Services; NLM is not responsible for the product and does not endorse or recommend this or any other product."
compute_ph_meds_estuse_flags_all(): Computes all medication estimated
use flags across all tables.
compute_ph_p_meds_estuse_flags_all(): Computes all medication estimated
use flags for the ph_p_meds table.
compute_ph_y_meds_estuse_flags_all(): Computes all medication estimated
use flags for the ph_y_meds table.
tbl. see combine parameter.
The medical estimated use values and categories are generated from: Lopez, D. A., Overholtzer, L. N., Rhee, K. E., Buchbinder, N., Ruiz-Orozco, G. E., Steinhilber, S., Tognoli, M., Lopez-Flores, A., & Nagel, B. J. (2025). Classifying and visualizing medication use in the Adolescent Brain Cognitive Development (ABCD) Study. medRxiv.
compute_ph_meds_catg_all(), rx_map
Computes the summary score ph_p_anthr__fath_height__cm
Anthropometrics [Parent] (Height): Father's height (cm)
Summarized variables:
ph_p_anthr__height__fath_001
ph_p_anthr__height__fath_001__01
Excluded values: None
Validation criterion: None
compute_ph_p_anthr__fath_height__cm( data, name = "ph_p_anthr__fath_height__cm", combine = TRUE )compute_ph_p_anthr__fath_height__cm( data, name = "ph_p_anthr__fath_height__cm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
compute_ph_p_anthr__fath_height__in()
## Not run: compute_ph_p_anthr__fath_height__cm(data) |> select( all_of(c("ph_p_anthr__fath_height__cm", vars_ph_p_anthr__height)) ) ## End(Not run)## Not run: compute_ph_p_anthr__fath_height__cm(data) |> select( all_of(c("ph_p_anthr__fath_height__cm", vars_ph_p_anthr__height)) ) ## End(Not run)
Computes the summary score ph_p_anthr__moth_height__cm
Anthropometrics [Parent] (Height): Mother's height (cm)
Summarized variables:
ph_p_anthr__height__moth_001
ph_p_anthr__height__moth_001__01
Excluded values: None
Validation criterion: None
compute_ph_p_anthr__moth_height__cm( data, name = "ph_p_anthr__moth_height__cm", combine = TRUE )compute_ph_p_anthr__moth_height__cm( data, name = "ph_p_anthr__moth_height__cm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
compute_ph_p_anthr__fath_height__in()
## Not run: compute_ph_p_anthr__moth_height__cm(data) |> select( all_of(c("ph_p_anthr__moth_height__cm", vars_ph_p_anthr__height)) ) ## End(Not run)## Not run: compute_ph_p_anthr__moth_height__cm(data) |> select( all_of(c("ph_p_anthr__moth_height__cm", vars_ph_p_anthr__height)) ) ## End(Not run)
Computes the summary score ph_p_anthr__moth_height__in
Anthropometrics [Parent] (Height): Mother's height (in)
Summarized variables:
ph_p_anthr__height__moth_001
ph_p_anthr__height__moth_001__01
Excluded values: None
Validation criterion: None
compute_ph_p_anthr__moth_height__in( data, name = "ph_p_anthr__moth_height__in", combine = TRUE )compute_ph_p_anthr__moth_height__in( data, name = "ph_p_anthr__moth_height__in", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
compute_ph_p_anthr__fath_height__in()
## Not run: compute_ph_p_anthr__moth_height__in(data) |> select( all_of(c("ph_p_anthr__moth_height__in", vars_ph_p_anthr__height)) ) ## End(Not run)## Not run: compute_ph_p_anthr__moth_height__in(data) |> select( all_of(c("ph_p_anthr__moth_height__in", vars_ph_p_anthr__height)) ) ## End(Not run)
ph_p_anthr summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_p_anthr_all(data)compute_ph_p_anthr_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_p_anthr_all(data) ## End(Not run)## Not run: compute_ph_p_anthr_all(data) ## End(Not run)
ph_p_cna summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_p_cna_all(data)compute_ph_p_cna_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_p_cna(data) ## End(Not run)## Not run: compute_ph_p_cna(data) ## End(Not run)
Computes the summary score ph_p_cna_sum
Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0
missing or declined]
Summarized variables:
ph_p_cna_001
ph_p_cna_002
ph_p_cna_003
ph_p_cna_004
ph_p_cna_005
ph_p_cna_006
ph_p_cna_007
ph_p_cna_008
ph_p_cna_009
ph_p_cna_010
ph_p_cna_011
ph_p_cna_012
ph_p_cna_013
ph_p_cna_014
Excluded values:
999
777
compute_ph_p_cna_nm( data, name = "ph_p_cna_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_cna_nm( data, name = "ph_p_cna_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_p_cna_nm(data) |> select( all_of(c("ph_p_cna_nm", vars_ph_p_cna)) ) ## End(Not run)## Not run: compute_ph_p_cna_nm(data) |> select( all_of(c("ph_p_cna_nm", vars_ph_p_cna)) ) ## End(Not run)
Computes the summary score ph_p_otbi__loc__30m_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness - Over 30 minutes): Number missing
Excluded values:
777
999
compute_ph_p_otbi__loc__30m_nm( data, name = "ph_p_otbi__loc__30m_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_otbi__loc__30m_nm( data, name = "ph_p_otbi__loc__30m_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_p_otbi__loc__30m_count()
Computes the summary score ph_p_otbi__loc__tbiage_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Age of first injury with LOC - Number missing
Excluded values:
777
999
Notes:
The output is set to NA when no head or neck injury/impact is reported
compute_ph_p_otbi__loc__tbiage_nm( data, name = "ph_p_otbi__loc__tbiage_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_otbi__loc__tbiage_nm( data, name = "ph_p_otbi__loc__tbiage_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_p_otbi__loc_tbiage()
Computes the summary score ph_p_otbi__loc_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Number missing
Excluded values:
777
999
compute_ph_p_otbi__loc_nm( data, name = "ph_p_otbi__loc_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_otbi__loc_nm( data, name = "ph_p_otbi__loc_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_p_otbi__loc_count()
Computes the summary score ph_p_otbi__rpt_nm
Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries):
Number missing
Excluded values:
777
999
compute_ph_p_otbi__rpt_nm( data, name = "ph_p_otbi__rpt_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_otbi__rpt_nm( data, name = "ph_p_otbi__rpt_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_p_otbi__rpt_count()
A single function to compute all scores in the above domain using default arguments.
compute_ph_p_otbi_all(data)compute_ph_p_otbi_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_p_otbi_all(data) ## End(Not run)## Not run: compute_ph_p_otbi_all(data) ## End(Not run)
Computes the summary score ph_p_pds__f__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Approximate tanner stages - Number missing
Summarized variables:
ph_p_pds_002
ph_p_pds__f_001
ph_p_pds__f_002
Excluded values:
777
999
compute_ph_p_pds__f__categ_nm( data, name = "ph_p_pds__f__categ_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_pds__f__categ_nm( data, name = "ph_p_pds__f__categ_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__f_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Number missing
Summarized variables:
ph_p_pds_001
ph_p_pds_002
ph_p_pds_003
ph_p_pds__f_001
ph_p_pds__f_002
Excluded values:
777
999
compute_ph_p_pds__f_nm( data, name = "ph_p_pds__f_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_pds__f_nm( data, name = "ph_p_pds__f_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__m__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Approximate tanner stages - Number missing
Summarized variables:
ph_p_pds_002
ph_p_pds__m_001
ph_p_pds__m_002
Excluded values:
777
999
compute_ph_p_pds__m__categ_nm( data, name = "ph_p_pds__m__categ_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_pds__m__categ_nm( data, name = "ph_p_pds__m__categ_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__m_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Number missing
Summarized variables:
ph_p_pds_001
ph_p_pds_002
ph_p_pds_003
ph_p_pds__m_001
ph_p_pds__m_002
Excluded values:
777
999
compute_ph_p_pds__m_nm( data, name = "ph_p_pds__m_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_pds__m_nm( data, name = "ph_p_pds__m_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
ph_p_pds summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_p_pds_all(data)compute_ph_p_pds_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_p_pds_all(data) ## End(Not run)## Not run: compute_ph_p_pds_all(data) ## End(Not run)
Computes the summary score ph_p_sds__da_nm
Sleep Disturbance Scale [Parent] (Disorder of arousal): Number missing
Summarized variables:
ph_p_sds__da_001
ph_p_sds__da_002
ph_p_sds__da_003
Excluded values:
777
999
compute_ph_p_sds__da_nm( data, name = "ph_p_sds__da_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__da_nm( data, name = "ph_p_sds__da_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__dims_nm
Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining
sleep): Number missing
Summarized variables:
ph_p_sds__dims_001
ph_p_sds__dims_002
ph_p_sds__dims_003
ph_p_sds__dims_004
ph_p_sds__dims_005
ph_p_sds__dims_006
ph_p_sds__dims_007
Excluded values:
777
999
compute_ph_p_sds__dims_nm( data, name = "ph_p_sds__dims_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__dims_nm( data, name = "ph_p_sds__dims_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__does_nm
Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence) -
Number missing
Summarized variables:
ph_p_sds__does_001
ph_p_sds__does_002
ph_p_sds__does_003
ph_p_sds__does_004
ph_p_sds__does_005
Excluded values:
777
999
compute_ph_p_sds__does_nm( data, name = "ph_p_sds__does_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__does_nm( data, name = "ph_p_sds__does_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__hyphy_nm
Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis): Number missing
Summarized variables:
ph_p_sds__hyphy_001
ph_p_sds__hyphy_002
Excluded values:
777
999
compute_ph_p_sds__hyphy_nm( data, name = "ph_p_sds__hyphy_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__hyphy_nm( data, name = "ph_p_sds__hyphy_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__sbd_nm
Sleep Disturbance Scale [Parent] (Sleep breathing disorders): Number missing
Summarized variables:
ph_p_sds__sbd_001
ph_p_sds__sbd_002
ph_p_sds__sbd_003
Excluded values:
777
999
compute_ph_p_sds__sbd_nm( data, name = "ph_p_sds__sbd_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__sbd_nm( data, name = "ph_p_sds__sbd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__swtd_nm
Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders): Number
missing
Summarized variables:
ph_p_sds__swtd_001
ph_p_sds__swtd_002
ph_p_sds__swtd_003
ph_p_sds__swtd_004
ph_p_sds__swtd_005
ph_p_sds__swtd_006
Excluded values:
777
999
compute_ph_p_sds__swtd_nm( data, name = "ph_p_sds__swtd_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds__swtd_nm( data, name = "ph_p_sds__swtd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
ph_p_sds summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_p_sds_all(data)compute_ph_p_sds_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_p_sds_all(data) ## End(Not run)## Not run: compute_ph_p_sds_all(data) ## End(Not run)
Computes the summary score ph_p_sds_nm
Sleep Disturbance Scale [Parent]: Number missing
Summarized variables:
ph_p_sds__dims_001
ph_p_sds__dims_002
ph_p_sds__dims_003
ph_p_sds__dims_004
ph_p_sds__dims_005
ph_p_sds__swtd_001
ph_p_sds__swtd_002
ph_p_sds__swtd_003
ph_p_sds__hyphy_001
ph_p_sds__dims_006
ph_p_sds__dims_007
ph_p_sds__swtd_004
ph_p_sds__sbd_001
ph_p_sds__sbd_002
ph_p_sds__sbd_003
ph_p_sds__hyphy_002
ph_p_sds__da_001
ph_p_sds__swtd_005
ph_p_sds__swtd_006
ph_p_sds__da_002
ph_p_sds__da_003
ph_p_sds__does_001
ph_p_sds__does_002
ph_p_sds__does_003
ph_p_sds__does_004
ph_p_sds__does_005
Excluded values:
777
999
compute_ph_p_sds_nm( data, name = "ph_p_sds_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_p_sds_nm( data, name = "ph_p_sds_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_anthr__height_nm
Anthropometrics [Youth] (Height): Number missing
Summarized variables:
ph_y_anthr__height__r01_001
ph_y_anthr__height__r02_001
ph_y_anthr__height__r03_001
Excluded values: none
compute_ph_y_anthr__height_nm( data, name = "ph_y_anthr__height_nm", combine = TRUE )compute_ph_y_anthr__height_nm( data, name = "ph_y_anthr__height_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_y_anthr__height_mean()
## Not run: compute_ph_y_anthr__height_nm(data) |> select( all_of(c("ph_y_anthr__height_nm", vars_ph_y_anthr__height)) ) ## End(Not run)## Not run: compute_ph_y_anthr__height_nm(data) |> select( all_of(c("ph_y_anthr__height_nm", vars_ph_y_anthr__height)) ) ## End(Not run)
Computes the summary score ph_y_anthr__weight_nm
Anthropometrics [Youth] (Weight): Number missing
Summarized variables:
ph_y_anthr__weight__r01_001
ph_y_anthr__weight__r02_001
ph_y_anthr__weight__r03_001
Excluded values: none
compute_ph_y_anthr__weight_nm( data, name = "ph_y_anthr__weight_nm", combine = TRUE )compute_ph_y_anthr__weight_nm( data, name = "ph_y_anthr__weight_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_ph_y_anthr__weight_mean()
## Not run: compute_ph_y_anthr__weight_nm(data) |> select( all_of(c("ph_y_anthr__weight_nm", vars_ph_y_anthr__weight)) ) ## End(Not run)## Not run: compute_ph_y_anthr__weight_nm(data) |> select( all_of(c("ph_y_anthr__weight_nm", vars_ph_y_anthr__weight)) ) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_y_anthr_all(data)compute_ph_y_anthr_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_y_anthr_all(data) ## End(Not run)## Not run: compute_ph_y_anthr_all(data) ## End(Not run)
Computes the summary score ph_y_bp__dia_nm
Blood Pressure [Youth] (Diastolic): Number missing
Summarized variables:
ph_y_bp__dia__r01_001
ph_y_bp__dia__r01_002
ph_y_bp__dia__r01_003
ph_y_bp__dia__r02_001
ph_y_bp__dia__r02_002
ph_y_bp__dia__r03_001
ph_y_bp__dia__r03_002
Excluded values: none
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
compute_ph_y_bp__dia_nm(data, name = "ph_y_bp__dia_nm", combine = TRUE)compute_ph_y_bp__dia_nm(data, name = "ph_y_bp__dia_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__dia_nm(data) |> select( all_of(c("ph_y_bp__dia_nm", vars_ph_y_bp__dia)) ) ## End(Not run)## Not run: compute_ph_y_bp__dia_nm(data) |> select( all_of(c("ph_y_bp__dia_nm", vars_ph_y_bp__dia)) ) ## End(Not run)
Computes the summary score ph_y_bp__hrate_nm
Blood Pressure [Youth] (Heart rate): Number missing
Summarized variables:
ph_y_bp__hrate__r01_001
ph_y_bp__hrate__r01_002
ph_y_bp__hrate__r01_003
ph_y_bp__hrate__r02_001
ph_y_bp__hrate__r02_002
ph_y_bp__hrate__r03_001
ph_y_bp__hrate__r03_002
Excluded values: none
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
compute_ph_y_bp__hrate_nm(data, name = "ph_y_bp__hrate_nm", combine = TRUE)compute_ph_y_bp__hrate_nm(data, name = "ph_y_bp__hrate_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__hrate_nm(data) |> select( all_of(c("ph_y_bp__hrate_nm", vars_ph_y_bp__hrate)) ) ## End(Not run)## Not run: compute_ph_y_bp__hrate_nm(data) |> select( all_of(c("ph_y_bp__hrate_nm", vars_ph_y_bp__hrate)) ) ## End(Not run)
Computes the summary score ph_y_bp__sys_nm
Blood Pressure [Youth] (Systolic): Number missing
Summarized variables:
ph_y_bp__sys__r01_001
ph_y_bp__sys__r01_002
ph_y_bp__sys__r01_003
ph_y_bp__sys__r02_001
ph_y_bp__sys__r02_002
ph_y_bp__sys__r03_001
ph_y_bp__sys__r03_002
Excluded values: none
There are at most 3 possible rounds of measurements, and the calculation is as follows:
if round 3 is available, use it, otherwise use round 2, otherwise use round 1
for round 3 and 2, there are at most 2 measurements
for round 1, there are at most 3 measurements:
participants with 3 measurements, and 0 missing, nm = 0
participants with 2 measurements, and 1 missing, nm = 1 - 1 = 0
participants with 1 measurement, and 2 missing, nm = 2 - 1 = 1
participants with 0 measurements, and 3 missing, nm = 3 - 1 = 2
compute_ph_y_bp__sys_nm(data, name = "ph_y_bp__sys_nm", combine = TRUE)compute_ph_y_bp__sys_nm(data, name = "ph_y_bp__sys_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__sys_nm(data) |> select( all_of(c("ph_y_bp__sys_nm", vars_ph_y_bp__sys)) ) ## End(Not run)## Not run: compute_ph_y_bp__sys_nm(data) |> select( all_of(c("ph_y_bp__sys_nm", vars_ph_y_bp__sys)) ) ## End(Not run)
This is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_y_bp_all(data)compute_ph_y_bp_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_y_bp_all(data) ## End(Not run)## Not run: compute_ph_y_bp_all(data) ## End(Not run)
Computes the summary score ph_y_mctq__fd__bed__end__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__end__24h_t (intermediate score)
ph_y_mctq__fd__sleep_inertia (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__bed__end__24h_t( data, name = "ph_y_mctq__fd__bed__end__24h_t", combine = TRUE )compute_ph_y_mctq__fd__bed__end__24h_t( data, name = "ph_y_mctq__fd__bed__end__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__bed__end__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__bed__end__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__bed__end__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__bed__end__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__bed__end__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed end): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__end__36h_t (intermediate score)
ph_y_mctq__fd__sleep_inertia (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__bed__end__36h_t( data, name = "ph_y_mctq__fd__bed__end__36h_t", combine = TRUE )compute_ph_y_mctq__fd__bed__end__36h_t( data, name = "ph_y_mctq__fd__bed__end__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__bed__end__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__bed__end__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__bed__end__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__bed__end__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__bed__start__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed start):
Time [24 hour adjusted]
Summarized variables:
ph_y_mctq__fd_001__02
ph_y_mctq__fd_001__01a
ph_y_mctq__fd_001__01b
Excluded values: none
compute_ph_y_mctq__fd__bed__start__24h_t( data, name = "ph_y_mctq__fd__bed__start__24h_t", combine = TRUE )compute_ph_y_mctq__fd__bed__start__24h_t( data, name = "ph_y_mctq__fd__bed__start__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__bed__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_001__02", "ph_y_mctq__fd_001__01a", "ph_y_mctq__fd_001__01b", "ph_y_mctq__fd__bed__start__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__bed__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_001__02", "ph_y_mctq__fd_001__01a", "ph_y_mctq__fd_001__01b", "ph_y_mctq__fd__bed__start__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__bed__start__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - In bed start):
Time [36 hour adjusted]
Summarized variables:
ph_y_mctq__fd_001__02
ph_y_mctq__fd_001__01a
ph_y_mctq__fd_001__01b
Excluded values: none
compute_ph_y_mctq__fd__bed__start__36h_t( data, name = "ph_y_mctq__fd__bed__start__36h_t", combine = TRUE )compute_ph_y_mctq__fd__bed__start__36h_t( data, name = "ph_y_mctq__fd__bed__start__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__bed__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_001__02", "ph_y_mctq__fd_001__01a", "ph_y_mctq__fd_001__01b", "ph_y_mctq__fd__bed__start__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__bed__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_001__02", "ph_y_mctq__fd_001__01a", "ph_y_mctq__fd_001__01b", "ph_y_mctq__fd__bed__start__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__bed_sum
Munich Chronotype Questionnaire [Youth] (Free Day - In bed): Sum
Summarized variables:
ph_y_mctq__fd__bed__end__36h_t (intermediate score)
ph_y_mctq__fd__bed__start__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__bed_sum( data, name = "ph_y_mctq__fd__bed_sum", combine = TRUE )compute_ph_y_mctq__fd__bed_sum( data, name = "ph_y_mctq__fd__bed_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__bed_sum(data) |> select( any_of(c( "ph_y_mctq__fd__bed_sum" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__bed_sum(data) |> select( any_of(c( "ph_y_mctq__fd__bed_sum" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__end__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__fd_005__02
ph_y_mctq__fd_005__01a
ph_y_mctq__fd_005__01b
Excluded values: none
compute_ph_y_mctq__fd__sleep__end__24h_t( data, name = "ph_y_mctq__fd__sleep__end__24h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__end__24h_t( data, name = "ph_y_mctq__fd__sleep__end__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep__end__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_005__02", "ph_y_mctq__fd_005__01a", "ph_y_mctq__fd_005__01b", "ph_y_mctq__fd__sleep__end__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep__end__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_005__02", "ph_y_mctq__fd_005__01a", "ph_y_mctq__fd_005__01b", "ph_y_mctq__fd__sleep__end__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__end__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep end): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__fd_005__02
ph_y_mctq__fd_005__01a
ph_y_mctq__fd_005__01b
Excluded values: none
compute_ph_y_mctq__fd__sleep__end__36h_t( data, name = "ph_y_mctq__fd__sleep__end__36h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__end__36h_t( data, name = "ph_y_mctq__fd__sleep__end__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep__end__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_005__02", "ph_y_mctq__fd_005__01a", "ph_y_mctq__fd_005__01b", "ph_y_mctq__fd__sleep__end__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep__end__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_005__02", "ph_y_mctq__fd_005__01a", "ph_y_mctq__fd_005__01b", "ph_y_mctq__fd__sleep__end__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__mid__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__onset__24h_t (intermediate score)
ph_y_mctq__fd__sleep_dur (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep__mid__24h_t( data, name = "ph_y_mctq__fd__sleep__mid__24h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__mid__24h_t( data, name = "ph_y_mctq__fd__sleep__mid__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep__mid__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__mid__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep__mid__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__mid__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__mid__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep mid): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__fd__sleep_period (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep__mid__36h_t( data, name = "ph_y_mctq__fd__sleep__mid__36h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__mid__36h_t( data, name = "ph_y_mctq__fd__sleep__mid__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep__mid__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__mid__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep__mid__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__mid__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__onset__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__start__24h_t (intermediate score)
ph_y_mctq__fd__sleep_latent (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep__onset__24h_t( data, name = "ph_y_mctq__fd__sleep__onset__24h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__onset__24h_t( data, name = "ph_y_mctq__fd__sleep__onset__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep__onset__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__onset__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep__onset__24h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__onset__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__onset__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep onset): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep__start__36h_t(intermediate score)
ph_y_mctq__fd__sleep_latent (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep__onset__36h_t( data, name = "ph_y_mctq__fd__sleep__onset__36h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__onset__36h_t( data, name = "ph_y_mctq__fd__sleep__onset__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep__onset__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__onset__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep__onset__36h_t(data) |> select( any_of(c( "ph_y_mctq__fd__sleep__onset__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__start__24h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__fd_002__02
ph_y_mctq__fd_002__01a
ph_y_mctq__fd_002__01b
Excluded values: none
compute_ph_y_mctq__fd__sleep__start__24h_t( data, name = "ph_y_mctq__fd__sleep__start__24h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__start__24h_t( data, name = "ph_y_mctq__fd__sleep__start__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_002__02", "ph_y_mctq__fd_002__01a", "ph_y_mctq__fd_002__01b", "ph_y_mctq__fd__sleep__start__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__fd_002__02", "ph_y_mctq__fd_002__01a", "ph_y_mctq__fd_002__01b", "ph_y_mctq__fd__sleep__start__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__start__36h_t
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep start): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__fd_002__02
ph_y_mctq__fd_002__01a
ph_y_mctq__fd_002__01b
Excluded values: none
compute_ph_y_mctq__fd__sleep__start__36h_t( data, name = "ph_y_mctq__fd__sleep__start__36h_t", combine = TRUE )compute_ph_y_mctq__fd__sleep__start__36h_t( data, name = "ph_y_mctq__fd__sleep__start__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_002__02", "ph_y_mctq__fd_002__01a", "ph_y_mctq__fd_002__01b", "ph_y_mctq__fd__sleep__start__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__fd_002__02", "ph_y_mctq__fd_002__01a", "ph_y_mctq__fd_002__01b", "ph_y_mctq__fd__sleep__start__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep__waso_sum
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep wakenings
after sleep onset): Sum
Summarized variables:
ph_y_mctq__fd_004
ph_y_mctq__fd_004__01
Excluded values: none
compute_ph_y_mctq__fd__sleep__waso_sum( data, name = "ph_y_mctq__fd__sleep__waso_sum", combine = TRUE )compute_ph_y_mctq__fd__sleep__waso_sum( data, name = "ph_y_mctq__fd__sleep__waso_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep__waso_sum(data) select( data, any_of(c( "ph_y_mctq__fd_004", "ph_y_mctq__fd_004__01", "ph_y_mctq__fd__sleep__waso_sum" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep__waso_sum(data) select( data, any_of(c( "ph_y_mctq__fd_004", "ph_y_mctq__fd_004__01", "ph_y_mctq__fd__sleep__waso_sum" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep_dur
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Duration
Summarized variables:
ph_y_mctq__fd__sleep__end__36h_t (intermediate score)
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__fd__sleep__waso_sum (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep_dur( data, name = "ph_y_mctq__fd__sleep_dur", combine = TRUE )compute_ph_y_mctq__fd__sleep_dur( data, name = "ph_y_mctq__fd__sleep_dur", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__fd__sleep_dur" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__fd__sleep_dur" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep_inertia
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Inertia
Summarized variables:
ph_y_mctq__fd_006
Excluded values: none
compute_ph_y_mctq__fd__sleep_inertia( data, name = "ph_y_mctq__fd__sleep_inertia", combine = TRUE )compute_ph_y_mctq__fd__sleep_inertia( data, name = "ph_y_mctq__fd__sleep_inertia", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep_inertia(data) select( data, any_of(c( "ph_y_mctq__fd_006", "ph_y_mctq__fd__sleep_inertia" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep_inertia(data) select( data, any_of(c( "ph_y_mctq__fd_006", "ph_y_mctq__fd__sleep_inertia" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep_latent
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Latency
Summarized variables:
ph_y_mctq__fd_003
Excluded values: none
compute_ph_y_mctq__fd__sleep_latent( data, name = "ph_y_mctq__fd__sleep_latent", combine = TRUE )compute_ph_y_mctq__fd__sleep_latent( data, name = "ph_y_mctq__fd__sleep_latent", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__fd__sleep_latent(data) select( data, any_of(c( "ph_y_mctq__fd_003", "ph_y_mctq__fd__sleep_latent" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__fd__sleep_latent(data) select( data, any_of(c( "ph_y_mctq__fd_003", "ph_y_mctq__fd__sleep_latent" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd__sleep_period
Munich Chronotype Questionnaire [Youth] (Free Day - Sleep): Period
Summarized variables:
ph_y_mctq__fd__sleep__end__36h_t (intermediate score)
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd__sleep_period( data, name = "ph_y_mctq__fd__sleep_period", combine = TRUE )compute_ph_y_mctq__fd__sleep_period( data, name = "ph_y_mctq__fd__sleep_period", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd__sleep_period(data) |> select( any_of(c( "ph_y_mctq__fd__sleep_period" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd__sleep_period(data) |> select( any_of(c( "ph_y_mctq__fd__sleep_period" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__fd_count
Munich Chronotype Questionnaire [Youth] (Free Day): Count
Summarized variables:
ph_y_mctq__sd_count (intermediate score)
Excluded values: none
compute_ph_y_mctq__fd_count(data, name = "ph_y_mctq__fd_count", combine = TRUE)compute_ph_y_mctq__fd_count(data, name = "ph_y_mctq__fd_count", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__fd_count(data) |> select( any_of(c( "ph_y_mctq__fd_count" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__fd_count(data) |> select( any_of(c( "ph_y_mctq__fd_count" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__raw__36h_chrono
Munich Chronotype Questionnaire [Youth] (Raw: Chronotype): Time [36
hour adjusted]
Summarized variables:
ph_y_mctq__fd__sleep_dur (intermediate score)
ph_y_mctq__sd__sleep_dur (intermediate score)
ph_y_mctq__fd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__sleep_dur (intermediate score)
Excluded values: none
compute_ph_y_mctq__raw__36h_chrono( data, name = "ph_y_mctq__raw__36h_chrono", combine = TRUE )compute_ph_y_mctq__raw__36h_chrono( data, name = "ph_y_mctq__raw__36h_chrono", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__raw__36h_chrono(data) |> select( any_of(c( "ph_y_mctq__raw__36h_chrono" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__raw__36h_chrono(data) |> select( any_of(c( "ph_y_mctq__raw__36h_chrono" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__school__leave__24h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__school_003__02
ph_y_mctq__school_003__01a
ph_y_mctq__school_003__01b
Excluded values: none
compute_ph_y_mctq__school__leave__24h_t( data, name = "ph_y_mctq__school__leave__24h_t", combine = TRUE )compute_ph_y_mctq__school__leave__24h_t( data, name = "ph_y_mctq__school__leave__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__school__leave__24h_t(data) select( data, any_of(c( "ph_y_mctq__school_003__02", "ph_y_mctq__school_003__01a", "ph_y_mctq__school_003__01b", "ph_y_mctq__school__leave__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__school__leave__24h_t(data) select( data, any_of(c( "ph_y_mctq__school_003__02", "ph_y_mctq__school_003__01a", "ph_y_mctq__school_003__01b", "ph_y_mctq__school__leave__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__school__leave__36h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule leave): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__school_003__02
ph_y_mctq__school_003__01a
ph_y_mctq__school_003__01b
Excluded values: none
compute_ph_y_mctq__school__leave__36h_t( data, name = "ph_y_mctq__school__leave__36h_t", combine = TRUE )compute_ph_y_mctq__school__leave__36h_t( data, name = "ph_y_mctq__school__leave__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__school__leave__36h_t(data) select( data, any_of(c( "ph_y_mctq__school_003__02", "ph_y_mctq__school_003__01a", "ph_y_mctq__school_003__01b", "ph_y_mctq__school__leave__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__school__leave__36h_t(data) select( data, any_of(c( "ph_y_mctq__school_003__02", "ph_y_mctq__school_003__01a", "ph_y_mctq__school_003__01b", "ph_y_mctq__school__leave__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__school__start__24h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__school_002__02
ph_y_mctq__school_002__01a
ph_y_mctq__school_002__01b
Excluded values: none
compute_ph_y_mctq__school__start__24h_t( data, name = "ph_y_mctq__school__start__24h_t", combine = TRUE )compute_ph_y_mctq__school__start__24h_t( data, name = "ph_y_mctq__school__start__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__school__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__school_002__02", "ph_y_mctq__school_002__01a", "ph_y_mctq__school_002__01b", "ph_y_mctq__school__start__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__school__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__school_002__02", "ph_y_mctq__school_002__01a", "ph_y_mctq__school_002__01b", "ph_y_mctq__school__start__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__school__start__36h_t
Munich Chronotype Questionnaire [Youth] ( School Schedule start): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__school_002__02
ph_y_mctq__school_002__01a
ph_y_mctq__school_002__01b
Excluded values: none
compute_ph_y_mctq__school__start__36h_t( data, name = "ph_y_mctq__school__start__36h_t", combine = TRUE )compute_ph_y_mctq__school__start__36h_t( data, name = "ph_y_mctq__school__start__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__school__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__school_002__02", "ph_y_mctq__school_002__01a", "ph_y_mctq__school_002__01b", "ph_y_mctq__school__start__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__school__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__school_002__02", "ph_y_mctq__school_002__01a", "ph_y_mctq__school_002__01b", "ph_y_mctq__school__start__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__bed__end__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed end):
Time [24 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__end__24h_t (intermediate score)
ph_y_mctq__sd__sleep_inertia (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__bed__end__24h_t( data, name = "ph_y_mctq__sd__bed__end__24h_t", combine = TRUE )compute_ph_y_mctq__sd__bed__end__24h_t( data, name = "ph_y_mctq__sd__bed__end__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__bed__end__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__bed__end__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__bed__end__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__bed__end__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__bed__end__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed end):
Time [36 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__end__36h_t (intermediate score)
ph_y_mctq__sd__sleep_inertia (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__bed__end__36h_t( data, name = "ph_y_mctq__sd__bed__end__36h_t", combine = TRUE )compute_ph_y_mctq__sd__bed__end__36h_t( data, name = "ph_y_mctq__sd__bed__end__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__bed__end__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__bed__end__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__bed__end__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__bed__end__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__bed__start__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed start):
Time [24 hour adjusted]
Summarized variables:
ph_y_mctq__sd_001__02
ph_y_mctq__sd_001__01a
ph_y_mctq__sd_001__01b
Excluded values: none
compute_ph_y_mctq__sd__bed__start__24h_t( data, name = "ph_y_mctq__sd__bed__start__24h_t", combine = TRUE )compute_ph_y_mctq__sd__bed__start__24h_t( data, name = "ph_y_mctq__sd__bed__start__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__bed__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_001__02", "ph_y_mctq__sd_001__01a", "ph_y_mctq__sd_001__01b", "ph_y_mctq__sd__bed__start__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__bed__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_001__02", "ph_y_mctq__sd_001__01a", "ph_y_mctq__sd_001__01b", "ph_y_mctq__sd__bed__start__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__bed__start__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - In bed start):
Time [36 hour adjusted]
Summarized variables:
ph_y_mctq__sd_001__02
ph_y_mctq__sd_001__01a
ph_y_mctq__sd_001__01b
Excluded values: none
compute_ph_y_mctq__sd__bed__start__36h_t( data, name = "ph_y_mctq__sd__bed__start__36h_t", combine = TRUE )compute_ph_y_mctq__sd__bed__start__36h_t( data, name = "ph_y_mctq__sd__bed__start__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__bed__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_001__02", "ph_y_mctq__sd_001__01a", "ph_y_mctq__sd_001__01b", "ph_y_mctq__sd__bed__start__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__bed__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_001__02", "ph_y_mctq__sd_001__01a", "ph_y_mctq__sd_001__01b", "ph_y_mctq__sd__bed__start__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__bed_sum
Munich Chronotype Questionnaire [Youth] (School Day - In bed): Sum
Summarized variables:
ph_y_mctq__sd__bed__end__36h_t (intermediate score)
ph_y_mctq__sd__bed__start__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__bed_sum( data, name = "ph_y_mctq__sd__bed_sum", combine = TRUE )compute_ph_y_mctq__sd__bed_sum( data, name = "ph_y_mctq__sd__bed_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__bed_sum(data) |> select( any_of(c( "ph_y_mctq__sd__bed_sum" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__bed_sum(data) |> select( any_of(c( "ph_y_mctq__sd__bed_sum" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__end__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__sd_005__02
ph_y_mctq__sd_005__01a
ph_y_mctq__sd_005__01b
Excluded values: none
compute_ph_y_mctq__sd__sleep__end__24h_t( data, name = "ph_y_mctq__sd__sleep__end__24h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__end__24h_t( data, name = "ph_y_mctq__sd__sleep__end__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep__end__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_005__02", "ph_y_mctq__sd_005__01a", "ph_y_mctq__sd_005__01b", "ph_y_mctq__sd__sleep__end__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep__end__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_005__02", "ph_y_mctq__sd_005__01a", "ph_y_mctq__sd_005__01b", "ph_y_mctq__sd__sleep__end__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__end__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep end): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__sd_005__02
ph_y_mctq__sd_005__01a
ph_y_mctq__sd_005__01b
Excluded values: none
compute_ph_y_mctq__sd__sleep__end__36h_t( data, name = "ph_y_mctq__sd__sleep__end__36h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__end__36h_t( data, name = "ph_y_mctq__sd__sleep__end__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep__end__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_005__02", "ph_y_mctq__sd_005__01a", "ph_y_mctq__sd_005__01b", "ph_y_mctq__sd__sleep__end__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep__end__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_005__02", "ph_y_mctq__sd_005__01a", "ph_y_mctq__sd_005__01b", "ph_y_mctq__sd__sleep__end__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__mid__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time
[24 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__onset__24h_t (intermediate score)
ph_y_mctq__sd__sleep_dur (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep__mid__24h_t( data, name = "ph_y_mctq__sd__sleep__mid__24h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__mid__24h_t( data, name = "ph_y_mctq__sd__sleep__mid__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep__mid__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__mid__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep__mid__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__mid__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__mid__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep mid): Time
[36 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__sd__sleep_period (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep__mid__36h_t( data, name = "ph_y_mctq__sd__sleep__mid__36h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__mid__36h_t( data, name = "ph_y_mctq__sd__sleep__mid__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep__mid__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__mid__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep__mid__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__mid__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__onset__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset):
Time [24 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__start__24h_t (intermediate score)
ph_y_mctq__sd__sleep_latent (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep__onset__24h_t( data, name = "ph_y_mctq__sd__sleep__onset__24h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__onset__24h_t( data, name = "ph_y_mctq__sd__sleep__onset__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep__onset__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__onset__24h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep__onset__24h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__onset__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__onset__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep onset):
Time [36 hour adjusted]
Summarized variables:
ph_y_mctq__sd__sleep__start__36h_t (intermediate score)
ph_y_mctq__sd__sleep_latent (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep__onset__36h_t( data, name = "ph_y_mctq__sd__sleep__onset__36h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__onset__36h_t( data, name = "ph_y_mctq__sd__sleep__onset__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep__onset__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__onset__36h_t" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep__onset__36h_t(data) |> select( any_of(c( "ph_y_mctq__sd__sleep__onset__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__start__24h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep start):
Time [24 hour adjusted]
Summarized variables:
ph_y_mctq__sd_002__02
ph_y_mctq__sd_002__01a
ph_y_mctq__sd_002__01b
Excluded values: none
compute_ph_y_mctq__sd__sleep__start__24h_t( data, name = "ph_y_mctq__sd__sleep__start__24h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__start__24h_t( data, name = "ph_y_mctq__sd__sleep__start__24h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_002__02", "ph_y_mctq__sd_002__01a", "ph_y_mctq__sd_002__01b", "ph_y_mctq__sd__sleep__start__24h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep__start__24h_t(data) select( data, any_of(c( "ph_y_mctq__sd_002__02", "ph_y_mctq__sd_002__01a", "ph_y_mctq__sd_002__01b", "ph_y_mctq__sd__sleep__start__24h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__start__36h_t
Munich Chronotype Questionnaire [Youth] (School Day - Sleep start):
Time [36 hour adjusted]
Summarized variables:
ph_y_mctq__sd_002__02
ph_y_mctq__sd_002__01a
ph_y_mctq__sd_002__01b
Excluded values: none
compute_ph_y_mctq__sd__sleep__start__36h_t( data, name = "ph_y_mctq__sd__sleep__start__36h_t", combine = TRUE )compute_ph_y_mctq__sd__sleep__start__36h_t( data, name = "ph_y_mctq__sd__sleep__start__36h_t", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_002__02", "ph_y_mctq__sd_002__01a", "ph_y_mctq__sd_002__01b", "ph_y_mctq__sd__sleep__start__36h_t" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep__start__36h_t(data) select( data, any_of(c( "ph_y_mctq__sd_002__02", "ph_y_mctq__sd_002__01a", "ph_y_mctq__sd_002__01b", "ph_y_mctq__sd__sleep__start__36h_t" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep__waso_sum
Munich Chronotype Questionnaire [Youth] (School Day - Sleep wakenings
after sleep onset): Sum
Summarized variables:
ph_y_mctq__sd_004
ph_y_mctq__sd_004__01
Excluded values: none
compute_ph_y_mctq__sd__sleep__waso_sum( data, name = "ph_y_mctq__sd__sleep__waso_sum", combine = TRUE )compute_ph_y_mctq__sd__sleep__waso_sum( data, name = "ph_y_mctq__sd__sleep__waso_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep__waso_sum(data) select( data, any_of(c( "ph_y_mctq__sd_004", "ph_y_mctq__sd_004__01", "ph_y_mctq__sd__sleep__waso_sum" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep__waso_sum(data) select( data, any_of(c( "ph_y_mctq__sd_004", "ph_y_mctq__sd_004__01", "ph_y_mctq__sd__sleep__waso_sum" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep_dur
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Duration
Summarized variables:
ph_y_mctq__sd__sleep__end__36h_t (intermediate score)
ph_y_mctq__sd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__sd__sleep__waso_sum (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep_dur( data, name = "ph_y_mctq__sd__sleep_dur", combine = TRUE )compute_ph_y_mctq__sd__sleep_dur( data, name = "ph_y_mctq__sd__sleep_dur", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__sd__sleep_dur" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__sd__sleep_dur" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep_inertia
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Inertia
Summarized variables:
ph_y_mctq__sd_006
Excluded values: none
compute_ph_y_mctq__sd__sleep_inertia( data, name = "ph_y_mctq__sd__sleep_inertia", combine = TRUE )compute_ph_y_mctq__sd__sleep_inertia( data, name = "ph_y_mctq__sd__sleep_inertia", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep_inertia(data) select( data, any_of(c( "ph_y_mctq__sd_006", "ph_y_mctq__sd__sleep_inertia" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep_inertia(data) select( data, any_of(c( "ph_y_mctq__sd_006", "ph_y_mctq__sd__sleep_inertia" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep_latent
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Latency
Summarized variables:
ph_y_mctq__sd_003
Excluded values: none
compute_ph_y_mctq__sd__sleep_latent( data, name = "ph_y_mctq__sd__sleep_latent", combine = TRUE )compute_ph_y_mctq__sd__sleep_latent( data, name = "ph_y_mctq__sd__sleep_latent", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd__sleep_latent(data) select( data, any_of(c( "ph_y_mctq__sd_003", "ph_y_mctq__sd__sleep_latent" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd__sleep_latent(data) select( data, any_of(c( "ph_y_mctq__sd_003", "ph_y_mctq__sd__sleep_latent" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd__sleep_period
Munich Chronotype Questionnaire [Youth] (School Day - Sleep): Period
Summarized variables:
ph_y_mctq__sd__sleep__end__36h_t (intermediate score)
ph_y_mctq__sd__sleep__onset__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__sd__sleep_period( data, name = "ph_y_mctq__sd__sleep_period", combine = TRUE )compute_ph_y_mctq__sd__sleep_period( data, name = "ph_y_mctq__sd__sleep_period", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sd__sleep_period(data) |> select( any_of(c( "ph_y_mctq__sd__sleep_period" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sd__sleep_period(data) |> select( any_of(c( "ph_y_mctq__sd__sleep_period" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sd_count
Munich Chronotype Questionnaire [Youth] (School Day): Count
Summarized variables:
ph_y_mctq__school_001
ph_y_mctq__school_001__01
ph_y_mctq__school_001__v01 (>= 7.0.0)
ph_y_mctq__school_001__01__v1 (>= 7.0.0)
Excluded values: none
compute_ph_y_mctq__sd_count(data, name = "ph_y_mctq__sd_count", combine = TRUE)compute_ph_y_mctq__sd_count(data, name = "ph_y_mctq__sd_count", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
In data release before 7.0 and 7.0.0 of the ABCDscores package,
the variables ph_y_mctq__school_001__v01 and
ph_y_mctq__school_001__01__v1 were
not available. In this case, the function will create
these variables internally and fill them with NA values.
After 7.0.0, these variables are expected to be present.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_ph_y_mctq__sd_count(data) select( data, any_of(c( "ph_y_mctq__school_001", "ph_y_mctq__school_001__01", "ph_y_mctq__school_001__v01", "ph_y_mctq__school_001__01__v1", "ph_y_mctq__sd_count" )) ) ## End(Not run)## Not run: data <- compute_ph_y_mctq__sd_count(data) select( data, any_of(c( "ph_y_mctq__school_001", "ph_y_mctq__school_001__01", "ph_y_mctq__school_001__v01", "ph_y_mctq__school_001__01__v1", "ph_y_mctq__sd_count" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sleep_dur
Munich Chronotype Questionnaire [Youth] (Sleep): Duration
Summarized variables:
ph_y_mctq__sd_count (intermediate score)
ph_y_mctq__sd__sleep_dur (intermediate score)
ph_y_mctq__fd__sleep_dur (intermediate score)
Excluded values: none
compute_ph_y_mctq__sleep_dur( data, name = "ph_y_mctq__sleep_dur", combine = TRUE )compute_ph_y_mctq__sleep_dur( data, name = "ph_y_mctq__sleep_dur", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__sleep_dur" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sleep_dur(data) |> select( any_of(c( "ph_y_mctq__sleep_dur" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sleep_loss
Munich Chronotype Questionnaire [Youth] (Sleep): Loss
Summarized variables:
ph_y_mctq__fd__sleep_period (intermediate score)
ph_y_mctq__sd__sleep_period (intermediate score)
ph_y_mctq__sd_count (intermediate score)
Excluded values: none
compute_ph_y_mctq__sleep_loss( data, name = "ph_y_mctq__sleep_loss", combine = TRUE )compute_ph_y_mctq__sleep_loss( data, name = "ph_y_mctq__sleep_loss", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sleep_loss(data) |> select( any_of(c( "ph_y_mctq__sleep_loss" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sleep_loss(data) |> select( any_of(c( "ph_y_mctq__sleep_loss" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__sleep_period
Munich Chronotype Questionnaire [Youth] (Sleep): Period
Summarized variables:
ph_y_mctq__sd_count (intermediate score)
ph_y_mctq__sd__sleep_period (intermediate score)
ph_y_mctq__fd__sleep_period (intermediate score)
Excluded values: none
compute_ph_y_mctq__sleep_period( data, name = "ph_y_mctq__sleep_period", combine = TRUE )compute_ph_y_mctq__sleep_period( data, name = "ph_y_mctq__sleep_period", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__sleep_period(data) |> select( any_of(c( "ph_y_mctq__sleep_period" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__sleep_period(data) |> select( any_of(c( "ph_y_mctq__sleep_period" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__socjl_absl
Munich Chronotype Questionnaire [Youth] (Social Jetlag: Absolute):
Time
Summarized variables:
ph_y_mctq__fd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__sd__sleep__mid__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__socjl_absl( data, name = "ph_y_mctq__socjl_absl", combine = TRUE )compute_ph_y_mctq__socjl_absl( data, name = "ph_y_mctq__socjl_absl", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__socjl_absl(data) |> select( any_of(c( "ph_y_mctq__socjl_absl" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__socjl_absl(data) |> select( any_of(c( "ph_y_mctq__socjl_absl" )) ) ## End(Not run)
Computes the summary score ph_y_mctq__socjl_rel
Munich Chronotype Questionnaire [Youth] (Social Jetlag: Relative):
Time
Summarized variables:
ph_y_mctq__fd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__sd__sleep__mid__36h_t (intermediate score)
Excluded values: none
compute_ph_y_mctq__socjl_rel( data, name = "ph_y_mctq__socjl_rel", combine = TRUE )compute_ph_y_mctq__socjl_rel( data, name = "ph_y_mctq__socjl_rel", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq__socjl_rel(data) |> select( any_of(c( "ph_y_mctq__socjl_rel" )) ) ## End(Not run)## Not run: compute_ph_y_mctq__socjl_rel(data) |> select( any_of(c( "ph_y_mctq__socjl_rel" )) ) ## End(Not run)
Compute all the MCTQ variables
compute_ph_y_mctq_all(data)compute_ph_y_mctq_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
Make sure the data is the full set of all variables from MCTQ.
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_y_mctq_all(data) ## End(Not run)## Not run: compute_ph_y_mctq_all(data) ## End(Not run)
Computes the summary score ph_y_mctq_chrono
Munich Chronotype Questionnaire [Youth] (Chronotype): Time
Summarized variables:
ph_y_mctq__fd_007
ph_y_mctq__fd__sleep_period (intermediate score)
ph_y_mctq__sd__sleep_period (intermediate score)
ph_y_mctq__fd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__sleep_period (intermediate score)
Excluded values: none
compute_ph_y_mctq_chrono(data, name = "ph_y_mctq_chrono", combine = TRUE)compute_ph_y_mctq_chrono(data, name = "ph_y_mctq_chrono", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq_chrono(data) |> select( any_of(c( "ph_y_mctq_chrono" )) ) ## End(Not run)## Not run: compute_ph_y_mctq_chrono(data) |> select( any_of(c( "ph_y_mctq_chrono" )) ) ## End(Not run)
Computes the summary score ph_y_mctq_outlier
Munich Chronotype Questionnaire [Youth]: Outlier
Summarized variables:
ph_y_mctq__sd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__fd__sleep__onset__36h_t (intermediate score)
ph_y_mctq__sd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__fd__sleep__mid__36h_t (intermediate score)
ph_y_mctq__sd__sleep_dur (intermediate score)
ph_y_mctq__fd__sleep_dur (intermediate score)
Excluded values: none
compute_ph_y_mctq_outlier(data, name = "ph_y_mctq_outlier", combine = TRUE)compute_ph_y_mctq_outlier(data, name = "ph_y_mctq_outlier", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_mctq_outlier(data) |> select( any_of(c( "ph_y_mctq_outlier" )) ) ## End(Not run)## Not run: compute_ph_y_mctq_outlier(data) |> select( any_of(c( "ph_y_mctq_outlier" )) ) ## End(Not run)
Computes the summary score ph_y_pds__f__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Approximate tanner stages - Number missing
Summarized variables:
ph_y_pds_002
ph_y_pds__f_001
ph_y_pds__f_002
Excluded values:
777
999
compute_ph_y_pds__f__categ_nm( data, name = "ph_y_pds__f__categ_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_y_pds__f__categ_nm( data, name = "ph_y_pds__f__categ_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__f_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Number missing
Summarized variables:
ph_y_pds_001
ph_y_pds_002
ph_y_pds_003
ph_y_pds__f_001
ph_y_pds__f_002
Excluded values:
777
999
compute_ph_y_pds__f_nm( data, name = "ph_y_pds__f_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_y_pds__f_nm( data, name = "ph_y_pds__f_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__m__categ_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Approximate tanner stages - Number missing
Summarized variables:
ph_y_pds_002
ph_y_pds__m_001
ph_y_pds__m_002
Excluded values:
777
999
compute_ph_y_pds__m__categ_nm( data, name = "ph_y_pds__m__categ_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_y_pds__m__categ_nm( data, name = "ph_y_pds__m__categ_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__m_nm
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Number missing
Summarized variables:
ph_y_pds_001
ph_y_pds_002
ph_y_pds_003
ph_y_pds__m_001
ph_y_pds__m_002
Excluded values:
777
999
compute_ph_y_pds__m_nm( data, name = "ph_y_pds__m_nm", exclude = c("777", "999"), combine = TRUE )compute_ph_y_pds__m_nm( data, name = "ph_y_pds__m_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
tbl. The input data frame with the summary score appended as a new column.
ph_y_pds summary scoresThis is a high-level function that computes all summary scores in this table.
Make sure the data contains all the necessary columns.
compute_ph_y_pds_all(data)compute_ph_y_pds_all(data)
data |
tbl. Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_ph_y_pds_all(data) ## End(Not run)## Not run: compute_ph_y_pds_all(data) ## End(Not run)
For each participant returns the age of onset for the requested substance(s). The function:
determines the session of first use (via compute_ss_use_onset_event())
and extracts the reported age at that visit;
for substance(s) that have detailed first-use age items, also extracts the earliest reported age of first use across the relevant substance-specific onset items; and
returns the age of first use if available, otherwise returns the age
reported at the visit. If neither value is available the result is NA.
compute_ss_use_onset_age(data, name, substance, algo = NULL)compute_ss_use_onset_age(data, name, substance, algo = NULL)
data |
tibble. A dataframe produced by |
name |
character(1). Name of the output score column to validate. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
|
algo |
character. Mapping algorithm to apply to mid‑year sessions. Allowed values:
|
A tibble with columns participant_id and a character
column named by name containing the age of onset or NA if there was no use.
## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_onset_age( name = "su_alc_onset_age", substance = "Alcohol" ) ## End(Not run)## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_onset_age( name = "su_alc_onset_age", substance = "Alcohol" ) ## End(Not run)
For each participant returns the session (character session_id) of first
use for the requested substance(s). The function:
maps or removes mid‑year sessions according to algo (see map_mid_years()) by default no.
for each participant selects the earliest session where any use was observed.
compute_ss_use_onset_event(data, name, substance, algo = NULL)compute_ss_use_onset_event(data, name, substance, algo = NULL)
data |
tibble. A dataframe produced by |
name |
character(1). Name of the output score column to validate. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
|
algo |
character. Mapping algorithm to apply to mid‑year sessions. Allowed values:
|
A tibble with columns participant_id and a character
column named by name containing the session of onset or NA if there was no use.
## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_onset_event( name = "su_alc_onset_event", substance = "Alcohol" ) ## End(Not run)## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_onset_event( name = "su_alc_onset_event", substance = "Alcohol" ) ## End(Not run)
For each participant computes a binary (1/0) indicator indicating any use
of (one of) the given substance(s) at a session (or cumulatively up to and
including that session when cumulative = TRUE).
Parameter algo is set to "next_existing_fy".
compute_ss_use_yn( data, name, substance, algo = "next_existing_fy", cumulative = FALSE )compute_ss_use_yn( data, name, substance, algo = "next_existing_fy", cumulative = FALSE )
data |
tibble. A dataframe produced by |
name |
character(1). Name of the output score column to validate. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
|
algo |
character. Mapping algorithm to apply to mid‑year sessions. Allowed values:
|
cumulative |
logical(1). If |
A tibble with columns participant_id, session_id and a numeric
column named by name containing 1 (use) or 0 (no use).
## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_yn( name = "su_y_alc_use_yn", substance = "Alcohol" ) ## End(Not run)## Not run: deap_data |> prepare_data_sdsu() |> compute_ss_use_yn( name = "su_y_alc_use_yn", substance = "Alcohol" ) ## End(Not run)
This function computes all summary scores for the su_p_ksads__aud table. Make sure to have all necessary columns in the data frame.
compute_su_p_ksads__aud_all(data)compute_su_p_ksads__aud_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the su_p_ksads__dud table. Make sure to have all necessary columns in the data frame.
compute_su_p_ksads__dud_all(data)compute_su_p_ksads__dud_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
Computes the summary score su_y_alcexp__neg_nm
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative
expectancies): Number missing
Summarized variables:
su_y_alcexp__neg_001
su_y_alcexp__neg_002
su_y_alcexp__neg_003
Excluded values: none
compute_su_y_alcexp__neg_nm(data, name = "su_y_alcexp__neg_nm", combine = TRUE)compute_su_y_alcexp__neg_nm(data, name = "su_y_alcexp__neg_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_alcexp__neg_prsum()
Computes the summary score su_y_alcexp__pos_nm
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive
expectancies): Number missing
Summarized variables:
su_y_alcexp__pos_001
su_y_alcexp__pos_002
su_y_alcexp__pos_003
Excluded values: none
compute_su_y_alcexp__pos_nm(data, name = "su_y_alcexp__pos_nm", combine = TRUE)compute_su_y_alcexp__pos_nm(data, name = "su_y_alcexp__pos_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_alcexp__pos_prsum()
A single function to compute all scores in the above domain using default arguments.
compute_su_y_alcexp_all(data)compute_su_y_alcexp_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_alcexp_all(data) ## End(Not run)## Not run: compute_su_y_alcexp_all(data) ## End(Not run)
compute all summary scores of Alcohol Hangover Symptoms Scale (HSS) Youth
compute_su_y_alchss_all(data)compute_su_y_alchss_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_alchss_all(data) ## End(Not run)## Not run: compute_su_y_alchss_all(data) ## End(Not run)
Computes the summary score su_y_alchss_count
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Count
Summarized variables:
su_y_alchss_001
su_y_alchss_002
su_y_alchss_003
su_y_alchss_004
su_y_alchss_005
su_y_alchss_006
su_y_alchss_007
su_y_alchss_008
su_y_alchss_009
su_y_alchss_010
su_y_alchss_011
su_y_alchss_012
su_y_alchss_013
su_y_alchss_014
su_y_alchss_001__l
su_y_alchss_002__l
su_y_alchss_003__l
su_y_alchss_004__l
su_y_alchss_005__l
su_y_alchss_006__l
su_y_alchss_007__l
su_y_alchss_008__l
su_y_alchss_009__l
su_y_alchss_010__l
su_y_alchss_011__l
su_y_alchss_012__l
su_y_alchss_013__l
su_y_alchss_014__l
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
compute_su_y_alchss_count( data, name = "su_y_alchss_count", max_na = 0, combine = TRUE )compute_su_y_alchss_count( data, name = "su_y_alchss_count", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_alchss_count(data) |> View() ## End(Not run)## Not run: compute_su_y_alchss_count(data) |> View() ## End(Not run)
Computes the summary score su_y_alchss_nm
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Number missing
Summarized variables:
su_y_alchss_001
su_y_alchss_002
su_y_alchss_003
su_y_alchss_004
su_y_alchss_005
su_y_alchss_006
su_y_alchss_007
su_y_alchss_008
su_y_alchss_009
su_y_alchss_010
su_y_alchss_011
su_y_alchss_012
su_y_alchss_013
su_y_alchss_014
su_y_alchss_001__l
su_y_alchss_002__l
su_y_alchss_003__l
su_y_alchss_004__l
su_y_alchss_005__l
su_y_alchss_006__l
su_y_alchss_007__l
su_y_alchss_008__l
su_y_alchss_009__l
su_y_alchss_010__l
su_y_alchss_011__l
su_y_alchss_012__l
su_y_alchss_013__l
su_y_alchss_014__l
Excluded values: none
compute_su_y_alchss_nm(data, name = "su_y_alchss_nm", combine = TRUE)compute_su_y_alchss_nm(data, name = "su_y_alchss_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_alchss_nm(data) ## End(Not run)## Not run: compute_su_y_alchss_nm(data) ## End(Not run)
A single function to compute all scores in the above domain using default arguments.
compute_su_y_alcprob_all(data)compute_su_y_alcprob_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_alcprob_all(data) ## End(Not run)## Not run: compute_su_y_alcprob_all(data) ## End(Not run)
Computes the summary score su_y_alcprob_nm
Alcohol Problem Index (RAPI) [Youth]: Number missing
Summarized variables:
ab_p_demo__race_001___0
ab_p_demo__race_001___10
ab_p_demo__race_001___11
ab_p_demo__race_001___12
ab_p_demo__race_001___13
ab_p_demo__race_001___14
ab_p_demo__race_001___15
ab_p_demo__race_001___16
ab_p_demo__race_001___17
ab_p_demo__race_001___18
ab_p_demo__race_001___19
ab_p_demo__race_001___20
ab_p_demo__race_001___21
ab_p_demo__race_001___22
ab_p_demo__race_001___23
ab_p_demo__race_001___24
ab_p_demo__race_001___25
ab_p_demo__race_001___777
ab_p_demo__race_001___999
ab_p_demo__race_001__v01___999
ab_p_demo__race_001__v01___10
ab_p_demo__race_001__v01___11
ab_p_demo__race_001__v01___12
ab_p_demo__race_001__v01___20
ab_p_demo__race_001__v01___21
ab_p_demo__race_001__v01___22
ab_p_demo__race_001__v01___23
ab_p_demo__race_001__v01___13
ab_p_demo__race_001__v01___14
ab_p_demo__race_001__v01___15
ab_p_demo__race_001__v01___17
ab_p_demo__race_001__v01___18
ab_p_demo__race_001__v01___19
ab_p_demo__race_001__v01___16
ab_p_demo__race_001__v01___24
ab_p_demo__race_001__v01___777
Excluded values: none
compute_su_y_alcprob_nm(data, name = "su_y_alcprob_nm", combine = TRUE)compute_su_y_alcprob_nm(data, name = "su_y_alcprob_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__6mo_count
Alcohol Subject Response and Effects [Youth] (Last 6 months): Count
[Validation: None missing or declined]
Summarized variables:
su_y_alcsre__6mo_001
su_y_alcsre__6mo_002
su_y_alcsre__6mo_003
su_y_alcsre__6mo_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
compute_su_y_alcsre__6mo_count( data, name = "su_y_alcsre__6mo_count", combine = TRUE, max_na = 0 )compute_su_y_alcsre__6mo_count( data, name = "su_y_alcsre__6mo_count", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__6mo_nm
Alcohol Subject Response and Effects [Youth] (Last 6 months): Number
missing
Summarized variables:
su_y_alcsre__6mo_001
su_y_alcsre__6mo_002
su_y_alcsre__6mo_003
su_y_alcsre__6mo_004
Excluded values: none
compute_su_y_alcsre__6mo_nm(data, name = "su_y_alcsre__6mo_nm", combine = TRUE)compute_su_y_alcsre__6mo_nm(data, name = "su_y_alcsre__6mo_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__first5_count
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Count [Validation: None missing or declined]
Summarized variables:
su_y_alcsre__first5_001
su_y_alcsre__first5_002
su_y_alcsre__first5_003
su_y_alcsre__first5_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
compute_su_y_alcsre__first5_count( data, name = "su_y_alcsre__first5_count", combine = TRUE, max_na = 0 )compute_su_y_alcsre__first5_count( data, name = "su_y_alcsre__first5_count", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__first5_nm
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Number missing
Summarized variables:
su_y_alcsre__first5_001
su_y_alcsre__first5_002
su_y_alcsre__first5_003
su_y_alcsre__first5_004
Excluded values: none
compute_su_y_alcsre__first5_nm( data, name = "su_y_alcsre__first5_nm", combine = TRUE )compute_su_y_alcsre__first5_nm( data, name = "su_y_alcsre__first5_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__hvy_count
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Count [Validation: None missing or declined]
Summarized variables:
su_y_alcsre__hvy_001
su_y_alcsre__hvy_002
su_y_alcsre__hvy_003
su_y_alcsre__hvy_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
compute_su_y_alcsre__hvy_count( data, name = "su_y_alcsre__hvy_count", combine = TRUE, max_na = 0 )compute_su_y_alcsre__hvy_count( data, name = "su_y_alcsre__hvy_count", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__hvy_nm
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Number missing
Summarized variables:
su_y_alcsre__hvy_001
su_y_alcsre__hvy_002
su_y_alcsre__hvy_003
su_y_alcsre__hvy_004
Excluded values: none
compute_su_y_alcsre__hvy_nm(data, name = "su_y_alcsre__hvy_nm", combine = TRUE)compute_su_y_alcsre__hvy_nm(data, name = "su_y_alcsre__hvy_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the su_y_alcsre form. Make sure to have all necessary columns in the data frame.
compute_su_y_alcsre_all(data)compute_su_y_alcsre_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_alcsre_all(data) ## End(Not run)## Not run: compute_su_y_alcsre_all(data) ## End(Not run)
Computes the summary score su_y_cigexp__neg_nm
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Number missing
Summarized variables:
su_y_cigexp__neg_001
su_y_cigexp__neg_002
Excluded values: none
compute_su_y_cigexp__neg_nm(data, name = "su_y_cigexp__neg_nm", combine = TRUE)compute_su_y_cigexp__neg_nm(data, name = "su_y_cigexp__neg_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_cigexp__neg_prsum()
Computes the summary score su_y_cigexp__neg_prsum__v01
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Prorated sum (v01)
Note: all 0s are changed to 1s prior to calculating pro-rated sum
Summarized variables:
su_y_cigexp__neg_001
su_y_cigexp__neg_002
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
compute_su_y_cigexp__neg_prsum__v01( data, name = "su_y_cigexp__neg_prsum__v01", combine = TRUE, max_na = 0 )compute_su_y_cigexp__neg_prsum__v01( data, name = "su_y_cigexp__neg_prsum__v01", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_cigexp__neg_prsum()
Computes the summary score su_y_cigexp__pos_nm
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Number missing
Summarized variables:
su_y_cigexp__pos_001
su_y_cigexp__pos_002
su_y_cigexp__pos_003
su_y_cigexp__pos_004
Excluded values: none
compute_su_y_cigexp__pos_nm(data, name = "su_y_cigexp__pos_nm", combine = TRUE)compute_su_y_cigexp__pos_nm(data, name = "su_y_cigexp__pos_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_cigexp__pos_prsum()
Computes the summary score su_y_cigexp__pos_prsum__v01
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Prorated sum (v01) [Validation: No more than 2
missing or declined]
Note: all 0s are changed to 1s prior to calculating pro-rated sum
Summarized variables:
su_y_cigexp__pos_001
su_y_cigexp__pos_002
su_y_cigexp__pos_003
su_y_cigexp__pos_004
Excluded values: none
Validation criterion: maximally 2 of 4 items missing
Notes:
Values in all input variables were recoded:
"0" –> "1"
compute_su_y_cigexp__pos_prsum__v01( data, name = "su_y_cigexp__pos_prsum__v01", combine = TRUE, max_na = 2 )compute_su_y_cigexp__pos_prsum__v01( data, name = "su_y_cigexp__pos_prsum__v01", combine = TRUE, max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_cigexp__pos_prsum()
A single function to compute all scores in the above domain using default arguments.
compute_su_y_cigexp_all(data)compute_su_y_cigexp_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_cigexp_all(data) ## End(Not run)## Not run: compute_su_y_cigexp_all(data) ## End(Not run)
A single function to compute all scores in the above domain using default arguments.
compute_su_y_drgprob_all(data)compute_su_y_drgprob_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_drgprob_all(data) ## End(Not run)## Not run: compute_su_y_drgprob_all(data) ## End(Not run)
Computes the summary score su_y_drgprob_nm
Drug Problem Index (DAPI) [Youth]: Number missing
Summarized variables:
su_y_drgprob_001
su_y_drgprob_002
su_y_drgprob_003
su_y_drgprob_004
su_y_drgprob_005
su_y_drgprob_006
su_y_drgprob_007
su_y_drgprob_008
su_y_drgprob_009
su_y_drgprob_010
su_y_drgprob_012
su_y_drgprob_013
su_y_drgprob_014
su_y_drgprob_015
su_y_drgprob_016
su_y_drgprob_017
su_y_drgprob_018
Excluded values: none
compute_su_y_drgprob_nm(data, name = "su_y_drgprob_nm", combine = TRUE)compute_su_y_drgprob_nm(data, name = "su_y_drgprob_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the su_y_ksads__aud table. Make sure to have all necessary columns in the data frame.
compute_su_y_ksads__aud_all(data)compute_su_y_ksads__aud_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
This function computes all summary scores for the su_y_ksads__dud table. Make sure to have all necessary columns in the data frame.
compute_su_y_ksads__dud_all(data)compute_su_y_ksads__dud_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
Computes the summary score su_y_mjexp__neg_nm
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative
expectancies): Number missing
Summarized variables:
su_y_mjexp__neg_001
su_y_mjexp__neg_002
su_y_mjexp__neg_003
Excluded values: none
compute_su_y_mjexp__neg_nm(data, name = "su_y_mjexp__neg_nm", combine = TRUE)compute_su_y_mjexp__neg_nm(data, name = "su_y_mjexp__neg_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_mjexp__neg_prsum()
Computes the summary score su_y_mjexp__pos_nm
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive
expectancies): Number missing
Summarized variables:
su_y_mjexp__pos_001
su_y_mjexp__pos_002
su_y_mjexp__pos_003
Excluded values: none
compute_su_y_mjexp__pos_nm(data, name = "su_y_mjexp__pos_nm", combine = TRUE)compute_su_y_mjexp__pos_nm(data, name = "su_y_mjexp__pos_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_mjexp__pos_prsum()
A single function to compute all scores in the above domain using default arguments.
compute_su_y_mjexp_all(data)compute_su_y_mjexp_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_mjexp_all(data) ## End(Not run)## Not run: compute_su_y_mjexp_all(data) ## End(Not run)
A single function to compute all scores in the above domain using default arguments.
compute_su_y_mjprob_all(data)compute_su_y_mjprob_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_mjprob_all(data) ## End(Not run)## Not run: compute_su_y_mjprob_all(data) ## End(Not run)
Computes the summary score su_y_mjprob_nm
Marijuana Problem Index (MAPI) [Youth]: Number missing
Summarized variables:
su_y_mjprob_001
su_y_mjprob_002
su_y_mjprob_003
su_y_mjprob_004
su_y_mjprob_005
su_y_mjprob_006
su_y_mjprob_007
su_y_mjprob_008
su_y_mjprob_009
su_y_mjprob_010
su_y_mjprob_011
su_y_mjprob_012
su_y_mjprob_016
su_y_mjprob_017
su_y_mjprob_018
Excluded values: none
compute_su_y_mjprob_nm(data, name = "su_y_mjprob_nm", combine = TRUE)compute_su_y_mjprob_nm(data, name = "su_y_mjprob_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjsre__neg_nm
Marijuana Subjective Response and Effects [Youth] (Negative): Number
missing
Summarized variables:
su_y_mjsre__neg_001
su_y_mjsre__neg_002
su_y_mjsre__neg_003
su_y_mjsre__neg_004
su_y_mjsre__neg_005
su_y_mjsre__neg_006
su_y_mjsre__neg_007
su_y_mjsre__neg_008
Excluded values: none
compute_su_y_mjsre__neg_nm(data, name = "su_y_mjsre__neg_nm", combine = TRUE)compute_su_y_mjsre__neg_nm(data, name = "su_y_mjsre__neg_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjsre__pos_nm
Marijuana Subjective Response and Effects [Youth] (Positive): Number
missing
Summarized variables:
su_y_mjsre__pos_001
su_y_mjsre__pos_002
su_y_mjsre__pos_003
Excluded values: none
compute_su_y_mjsre__pos_nm(data, name = "su_y_mjsre__pos_nm", combine = TRUE)compute_su_y_mjsre__pos_nm(data, name = "su_y_mjsre__pos_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the su_y_mjsre form. Make sure to have all necessary columns in the data frame.
compute_su_y_mjsre_all(data)compute_su_y_mjsre_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_mjsre_all(data) ## End(Not run)## Not run: compute_su_y_mjsre_all(data) ## End(Not run)
Computes the summary score su_y_mjsre_nm
Marijuana Subjective Response and Effects [Youth] (NA): Number missing
Summarized variables:
su_y_mjsre__pos_001
su_y_mjsre__pos_002
su_y_mjsre__pos_003
su_y_mjsre__neg_001
su_y_mjsre__neg_002
su_y_mjsre__neg_003
su_y_mjsre__neg_004
su_y_mjsre__neg_005
su_y_mjsre__neg_006
su_y_mjsre__neg_007
su_y_mjsre__neg_008
Excluded values: none
compute_su_y_mjsre_nm(data, name = "su_y_mjsre_nm", combine = TRUE)compute_su_y_mjsre_nm(data, name = "su_y_mjsre_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__chew_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first smokeless tobacco or chew use): Number missing
Summarized variables:
su_y_nicsre__chew__pos_001
su_y_nicsre__chew__neg_001
Excluded values: none
compute_su_y_nicsre__chew_nm( data, name = "su_y_nicsre__chew_nm", combine = TRUE )compute_su_y_nicsre__chew_nm( data, name = "su_y_nicsre__chew_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__cig_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first cigarette use): Number missing
Summarized variables:
su_y_nicsre__cig__pos_001
su_y_nicsre__cig__neg_001
Excluded values: none
compute_su_y_nicsre__cig_nm(data, name = "su_y_nicsre__cig_nm", combine = TRUE)compute_su_y_nicsre__cig_nm(data, name = "su_y_nicsre__cig_nm", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__vape_nm
Nicotine Subjective Response and Effects [Youth] (Positive and
negative effects of first vape use): Number missing
Summarized variables:
su_y_nicsre__vape__pos_001
su_y_nicsre__vape__pos_001__v01
su_y_nicsre__vape__neg_001
su_y_nicsre__vape__neg_001__v01
Excluded values: none
compute_su_y_nicsre__vape_nm( data, name = "su_y_nicsre__vape_nm", combine = TRUE )compute_su_y_nicsre__vape_nm( data, name = "su_y_nicsre__vape_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
tbl. The input data frame with the summary score appended as a new column.
This function computes all summary scores for the su_y_nicsre form. Make sure to have all necessary columns in the data frame.
compute_su_y_nicsre_all(data)compute_su_y_nicsre_all(data)
data |
tbl. Data frame containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_nicsre_all(data) ## End(Not run)## Not run: compute_su_y_nicsre_all(data) ## End(Not run)
Computes the summary score su_y_nicvapeexp__neg_nm
ENDS Expectancies [Youth] (Strength of negative expectancies): Number
missing
Summarized variables:
su_y_nicvapeexp__neg_001
su_y_nicvapeexp__neg_002
su_y_nicvapeexp__neg_003
su_y_nicvapeexp__neg_004
Excluded values: none
compute_su_y_nicvapeexp__neg_nm( data, name = "su_y_nicvapeexp__neg_nm", combine = TRUE )compute_su_y_nicvapeexp__neg_nm( data, name = "su_y_nicvapeexp__neg_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_nicvapeexp__neg_prsum()
Computes the summary score su_y_nicvapeexp__pos_nm
ENDS Expectancies [Youth] (Strength of positive expectancies): Number
missing
Summarized variables:
su_y_nicvapeexp__pos_001
su_y_nicvapeexp__pos_002
su_y_nicvapeexp__pos_003
su_y_nicvapeexp__pos_004
Excluded values: none
compute_su_y_nicvapeexp__pos_nm( data, name = "su_y_nicvapeexp__pos_nm", combine = TRUE )compute_su_y_nicvapeexp__pos_nm( data, name = "su_y_nicvapeexp__pos_nm", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
tbl. The input data frame with the summary score appended as a new column.
compute_su_y_nicvapeexp__pos_prsum()
A single function to compute all scores in the above domain using default arguments.
compute_su_y_nicvapeexp_all(data)compute_su_y_nicvapeexp_all(data)
data |
tbl, Dataframe containing the columns to be summarized. |
tbl. The input data frame with the summary scores appended as new columns.
## Not run: compute_su_y_nicvapeexp_all(data) ## End(Not run)## Not run: compute_su_y_nicvapeexp_all(data) ## End(Not run)
Computes the number of days since the last use of a given substance
as of the day of the substance use interview.
Returns NA for the participants with no reported use of the provided
substance.
compute_su_y_sui__last__day_count(data, name, substance, combine = TRUE)compute_su_y_sui__last__day_count(data, name, substance, combine = TRUE)
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_sui__last__day_count( data = data_sui, name = "su_y_sui__alc__last__day_count", substance = "alc" ) ## End(Not run)## Not run: compute_su_y_sui__last__day_count( data = data_sui, name = "su_y_sui__alc__last__day_count", substance = "alc" ) ## End(Not run)
Computes the age (in years) of regular use of a given substance.
Returns NA for the participants with no regular use of the provided
substance reported.
compute_su_y_sui__reg_useage(data, name, substance, combine = TRUE)compute_su_y_sui__reg_useage(data, name, substance, combine = TRUE)
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_sui__reg_useage( data = data_sui, name = "su_y_sui__alc__reg_useage", substance = "alc" ) ## End(Not run)## Not run: compute_su_y_sui__reg_useage( data = data_sui, name = "su_y_sui__alc__reg_useage", substance = "alc" ) ## End(Not run)
Computes either the first or last date of use for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_dt( data, name, substance = NULL, period = NULL, days = NULL, co_use = NULL, binge = NULL, position )compute_tlfb_dt( data, name, substance = NULL, period = NULL, days = NULL, co_use = NULL, binge = NULL, position )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
position |
character. The position of the substance use event. Must be
one of |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_dt( data = data_tlfb, name = "su_y_tlfb__alc__first__cum_dt", substance = "Alcohol", position = "first" ) ## End(Not run)## Not run: compute_tlfb_dt( data = data_tlfb, name = "su_y_tlfb__alc__first__cum_dt", substance = "Alcohol", position = "first" ) ## End(Not run)
Computes the maximum dose over all use days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_maxdose( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )compute_tlfb_maxdose( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_maxdose( data = data_tlfb, name = "su_y_tlfb__alc__3mo_maxdose", substance = "Alcohol", days = 90 ) ## End(Not run)## Not run: compute_tlfb_maxdose( data = data_tlfb, name = "su_y_tlfb__alc__3mo_maxdose", substance = "Alcohol", days = 90 ) ## End(Not run)
Computes the mean quantity per use day for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_mean( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )compute_tlfb_mean( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_mean( data = data_tlfb, name = "su_y_tlfb__alc__1mo_mean", substance = "Alcohol", days = 30 ) ## End(Not run)## Not run: compute_tlfb_mean( data = data_tlfb, name = "su_y_tlfb__alc__1mo_mean", substance = "Alcohol", days = 30 ) ## End(Not run)
Computes the total dose over all use day for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_totdose( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )compute_tlfb_totdose( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_totdose( data = data_tlfb, name = "su_y_tlfb__alc__binge_totdose", substance = "Alcohol", binge = list("F" = 4, "M" = 5) ) ## End(Not run)## Not run: compute_tlfb_totdose( data = data_tlfb, name = "su_y_tlfb__alc__binge_totdose", substance = "Alcohol", binge = list("F" = 4, "M" = 5) ) ## End(Not run)
Computes the lifetime total dose over all use day for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_totdose_sum( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )compute_tlfb_totdose_sum( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_totdose_sum( data = data_tlfb, name = "su_y_tlfb__alc__totdose_sum", substance = "Alcohol" ) ## End(Not run)## Not run: compute_tlfb_totdose_sum( data = data_tlfb, name = "su_y_tlfb__alc__totdose_sum", substance = "Alcohol" ) ## End(Not run)
Computes the number of use days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; only considering specific day types (weekends or week days); only considering days with co-use of (a)other substance(s); and/or only binge use.
compute_tlfb_ud( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )compute_tlfb_ud( data, name, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_ud( data = data_tlfb, name = "su_y_tlfb__alc__1mo__wknd_ud", substance = "Alcohol", days = 30, wknd = TRUE ) ## End(Not run)## Not run: compute_tlfb_ud( data = data_tlfb, name = "su_y_tlfb__alc__1mo__wknd_ud", substance = "Alcohol", days = 30, wknd = TRUE ) ## End(Not run)
Utility function to convert MCTQ survey responses to 24h or 36h format times.
convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, scale = "24h")convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, scale = "24h")
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the new column with the summary score. |
col_hrs_a |
character. The name of the column with the first time. 1, 4 AM | 2, 5 AM | 3, 6 AM | 4, 7 AM | 5, 8 AM | 6, 9 AM | 7, 10 AM | 8, 11 AM | 9, 12 PM | 10, 1 PM | 11, 2 PM | 12, 3 PM | 13, 4 PM |
col_hrs_b |
character. The name of the column with the second time. 1, 5 PM | 2, 6 PM | 3, 7 PM | 4, 8 PM | 5, 9 PM | 6, 10 PM | 7, 11 PM | 8, 12 AM | 9, 1 AM | 10, 2 AM | 11, 3 AM |
col_minute |
character. The name of the column with the minutes. If the
column value is 1, 0 minutes | 2, 5 minutes | 3, 10 minutes | 4, 15 minutes | 5, 20 minutes | 6, 25 minutes | 7, 30 minutes | 8, 35 minutes | 9, 40 minutes | 10, 45 minutes | 11, 50 minutes | 12, 55 minutes |
scale |
character. The scale of the time format. Default is "24h". The other option is "36h". |
Expect values 0 <= value < 24 for 24h format. Expect values 12 <= value < 36 for 36h format.
tbl. The input data frame with the summary score appended as a new column.
col_hrs_a <- "ph_y_mctq__fd_001__01a" col_hrs_b <- "ph_y_mctq__fd_001__01b" col_minute <- "ph_y_mctq__fd_001__02" name <- "ph_y_mctq__fd__bed__start__24h_t" data <- dplyr::tibble( ph_y_mctq__fd_001__01a = c(NA, NA, NA, NA, NA, 1, 7, 3, NA), ph_y_mctq__fd_001__01b = c(6, 7, 8, 8, 10, NA, NA, NA, NA), ph_y_mctq__fd_001__02 = c(1, 1, 1, 7, 7, 1, 4, 1, NA) ) convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute) name <- "ph_y_mctq__fd__bed__start__36h_t" convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, "36h")col_hrs_a <- "ph_y_mctq__fd_001__01a" col_hrs_b <- "ph_y_mctq__fd_001__01b" col_minute <- "ph_y_mctq__fd_001__02" name <- "ph_y_mctq__fd__bed__start__24h_t" data <- dplyr::tibble( ph_y_mctq__fd_001__01a = c(NA, NA, NA, NA, NA, 1, 7, 3, NA), ph_y_mctq__fd_001__01b = c(6, 7, 8, 8, 10, NA, NA, NA, NA), ph_y_mctq__fd_001__02 = c(1, 1, 1, 7, 7, 1, 4, 1, NA) ) convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute) name <- "ph_y_mctq__fd__bed__start__36h_t" convert_time_mctq(data, name, col_hrs_a, col_hrs_b, col_minute, "36h")
Creates a new column which contains the parsed numeric value for the visit. Annual visits are set to integers, where 0 = baseline, 1 = year 1, and so on. Mid-years are defined as 0.5 increments of the prior annual visits, e.g., 0.5 = between baseline and year 1, 1.5 = between year 1 and 2, and so on.
create_session_num(data, name = "session_num")create_session_num(data, name = "session_num")
data |
tbl. Data frame containing the |
name |
character of length 1. The name of the newly created and appended
column. Default: |
tbl. The input data frame with the name column added.
# Example data dat <- tibble::tibble( participant_id = c("A123", "A123", "A123", "A123"), session_id = c("ses-00S", "ses-00A", "ses-00M", "ses-01A"), a = c(1, 2, 3, 4), b = c(10, 11, 12, NA) ) # Create a new column (default: `session_num`) with numeric session create_session_num( dat ) # Create a new column called `num` that contains the session numbers create_session_num( dat, name = "num" )# Example data dat <- tibble::tibble( participant_id = c("A123", "A123", "A123", "A123"), session_id = c("ses-00S", "ses-00A", "ses-00M", "ses-01A"), a = c(1, 2, 3, 4), b = c(10, 11, 12, NA) ) # Create a new column (default: `session_num`) with numeric session create_session_num( dat ) # Create a new column called `num` that contains the session numbers create_session_num( dat, name = "num" )
This function filters the TLFB (Timeline Followback) data based on specified substance(s); period (estimated vs. detailed); number of days before the TLFB interview; weekend-only usage; co-use of other substances; and/or binge use.
filter_tlfb( data, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )filter_tlfb( data, substance = NULL, period = NULL, days = NULL, wknd = NULL, co_use = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
wknd |
logical. Whether the score should be computed for weekends only
( |
co_use |
character (vector). Co-use substance(s). Must be one or several
of the possible values for |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
A filtered data frame based on the specified criteria.
## Not run: filtered_data <- filter_tlfb( data, substance = "Alcohol", wknd_only = TRUE, period = "estimated", days = 30 ) ## End(Not run)## Not run: filtered_data <- filter_tlfb( data, substance = "Alcohol", wknd_only = TRUE, period = "estimated", days = 30 ) ## End(Not run)
This function retrieves the tscore table from a list of tscores based on the function name. The function should be used internally.
get_tscore_tbl(list_tscore, func_name)get_tscore_tbl(list_tscore, func_name)
list_tscore |
list. List of tscores. see details. |
func_name |
character. The name of the function. |
The list_tscore should be a list of prepared tscore tables. The list has
two layers of structure: the first layer is the name of form, and the second
layer is the keyword of the tscore table.
list |- form_1 | |- keyword_1 | |- keyword_2 | |- ... |- form_2 | |- keyword_1 | |- keyword_2 | |- ... |- ...
This object is prepared by the DSM team and for internal users, please ask
the DSM team for the rds file.
Forms and keywords are based on the function names. A function should contain
both the form and keyword in its name, with only one exception being the
overall score of a form, which does not have a keyword. The function name
should be in the format of compute_form_xx__keyword_tscore or
compute_form_xx_tscore. The function name will be split by _ and
the unique keywords will be used to search for the tscore table.
tbl. The tscore table. If there is no match or more than one match, an error will be thrown.
## Not run: list_tscore <- readRDS("aseba_tscore.rds") get_tscore_tbl(list_tscore, "compute_mh_p_abcl__afs__frnd_tscore") ## End(Not run)## Not run: list_tscore <- readRDS("aseba_tscore.rds") get_tscore_tbl(list_tscore, "compute_mh_p_abcl__afs__frnd_tscore") ## End(Not run)
Update an existing field to include longitudinal responses.
Use data for each id from the first available event and
set that value for all event rows.
make_static( data, id = "participant_id", event = "session_id", exclude = NULL, var_in, var_out )make_static( data, id = "participant_id", event = "session_id", exclude = NULL, var_in, var_out )
data |
Dataframe with fields specified in |
id |
character of length 1. Name of field that contains the IDs for which we need to assess the longitudinal data. |
event |
character of length 1. Name of field that contains the (longitudinal) event IDs. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
var_in |
character of length 1. Name of the field that contains the longitudinal values or responses. |
var_out |
character of length 1. Name of the new field that contains
one static value per |
Dataframe with two columns: id and var_out
data <- tibble::tribble( ~"id", ~"event", ~"values", "A", 1, NA, "A", 2, 2, "A", 3, 3, "B", 1, NA, "B", 2, NA, "B", 3, 1 ) make_static( data, var_in = "values", var_out = "static_nothing_excluded", id = "id", event = "event" ) make_static( data, var_in = "values", var_out = "static_excluding_1and2", exclude = c("1", "2"), id = "id", event = "event" )data <- tibble::tribble( ~"id", ~"event", ~"values", "A", 1, NA, "A", 2, 2, "A", 3, 3, "B", 1, NA, "B", 2, NA, "B", 3, 1 ) make_static( data, var_in = "values", var_out = "static_nothing_excluded", id = "id", event = "event" ) make_static( data, var_in = "values", var_out = "static_excluding_1and2", exclude = c("1", "2"), id = "id", event = "event" )
Creates a bullet point list in markdown format. Copy of
gluedown::md_bullet() but with the added ability to specify an indent to
create nested lists and the option to use code font.
md_bullet( x, indent = 0, code = FALSE, italic = FALSE, marker = c("*", "-", "+") )md_bullet( x, indent = 0, code = FALSE, italic = FALSE, marker = c("*", "-", "+") )
x |
character (vector). Text to convert into a bullet point list. |
indent |
numeric, positive whole number. Number of spaces to indent the bullet point list by (Default: 0). |
code |
logical. If the text will be formatted as code (Default: TRUE). |
italic |
logical. If the text will be formatted as italic (Default: FALSE). |
marker |
character. The bullet list marker to use (Default: "*"). |
glue vector. A bullet point list in markdown format.
md_bullet(c("First item", "Second item", "Third item"), code = TRUE) md_bullet(c("First item", "Second item", "Third item"), indent = 2)md_bullet(c("First item", "Second item", "Third item"), code = TRUE) md_bullet(c("First item", "Second item", "Third item"), indent = 2)
Recodes specified levels of a character/factor variable, e.g., to apply reverse coding before summary score computation.
recode_levels(data, vars, recode, temp = FALSE)recode_levels(data, vars, recode, temp = FALSE)
data |
tbl. Data frame containing the columns to be recoded. |
vars |
character (vector). The name(s) of the column(s) to be recoded. |
recode |
named character vector. The levels to be recoded, with the name being the original value and the value being the value to recode to. |
temp |
logical. If |
tbl. The input data frame with the recoded variable(s).
data <- tibble::tibble( var_a = c("1", "2", "3", "4", "5", NA, "999", "777"), var_b = c("5", "4", "3", "2", "1", "777", NA, "999") ) # recode individual variables data |> recode_levels( vars = "var_a", recode = c("999" = "0", "777" = "0") ) |> recode_levels( vars = "var_b", recode = c("999" = "6", "777" = "7") ) # apply the same recoding to several variables data |> recode_levels( vars = c( "var_a", "var_b" ), recode = c( "1" = "5", "2" = "4", "4" = "2", "5" = "1" ) )data <- tibble::tibble( var_a = c("1", "2", "3", "4", "5", NA, "999", "777"), var_b = c("5", "4", "3", "2", "1", "777", NA, "999") ) # recode individual variables data |> recode_levels( vars = "var_a", recode = c("999" = "0", "777" = "0") ) |> recode_levels( vars = "var_b", recode = c("999" = "6", "777" = "7") ) # apply the same recoding to several variables data |> recode_levels( vars = c( "var_a", "var_b" ), recode = c( "1" = "5", "2" = "4", "4" = "2", "5" = "1" ) )
Computes the number of conditions (provided as a character vectorcond),
involving the input variables vars, that were found to be TRUE.
Options available to exclude certain values from the input variables
(provided as a character vector exclude).
ss_count( data, name, vars, vars_temp = NULL, exclude = NULL, combine = FALSE, allow_missingness = TRUE, cond )ss_count( data, name, vars, vars_temp = NULL, exclude = NULL, combine = FALSE, allow_missingness = TRUE, cond )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The name(s) of the column(s) to be summarized. |
vars_temp |
character vector. The name(s) of temporary column(s) used
to compute the summary score. Note, these columns are not checked for
missingness. See |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: FALSE). |
allow_missingness |
logical. Default set to TRUE. If TRUE, summary score
is set to |
cond |
character vector. Each specified condition, involving the values
of specific input fields, gets tested for |
tbl. The input data frame with the summary score appended as a new column.
dat <- tibble::tibble( id = c("1", "2", "3", "4", "5", "6", "7", "8"), a_1 = c(1, 1, NA, 1, 1, 1, 1, 1), a_2 = c(1, NA, NA, 1, 1, NA, 1, 1), b_1 = c(1, 1, NA, NA, 1, 1, 1, 1), b_2 = c(1, 1, NA, 1, 1, NA, 1, 1), c = c(NA, 1, NA, 1, 777, 0, 1, 0) ) # define conditions to assess conditions <- c( "a_1 == 1 & a_2 == 1", "b_1 == 1 & b_2 == 1", "c" ) # count number of matched conditions ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, combine = TRUE ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), combine = TRUE ) conditions <- paste( c( "a_1 == 1 & a_2 == 1", "b_1 == 1 & b_2 == 1", "c >= 1" ), collapse = "&" ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), combine = TRUE ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), allow_missingness = FALSE, combine = TRUE )dat <- tibble::tibble( id = c("1", "2", "3", "4", "5", "6", "7", "8"), a_1 = c(1, 1, NA, 1, 1, 1, 1, 1), a_2 = c(1, NA, NA, 1, 1, NA, 1, 1), b_1 = c(1, 1, NA, NA, 1, 1, 1, 1), b_2 = c(1, 1, NA, 1, 1, NA, 1, 1), c = c(NA, 1, NA, 1, 777, 0, 1, 0) ) # define conditions to assess conditions <- c( "a_1 == 1 & a_2 == 1", "b_1 == 1 & b_2 == 1", "c" ) # count number of matched conditions ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, combine = TRUE ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), combine = TRUE ) conditions <- paste( c( "a_1 == 1 & a_2 == 1", "b_1 == 1 & b_2 == 1", "c >= 1" ), collapse = "&" ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), combine = TRUE ) ss_count( data = dat, name = "ss", vars = c("a_1", "a_2", "b_1", "b_2", "c"), cond = conditions, exclude = c("777"), allow_missingness = FALSE, combine = TRUE )
Computes the number of conditions (provided as a character vectorcond),
involving the input variables vars, that were found to be TRUE.
Options available to exclude certain values from the input variables
(provided as a character vector exclude).
ss_count_cond(data, name, vars, exclude = NULL, combine = FALSE, cond, max_na)ss_count_cond(data, name, vars, exclude = NULL, combine = FALSE, cond, max_na)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: FALSE). |
cond |
character vector. Each specified condition, involving the values
of specific input fields, gets tested for |
max_na |
numeric, positive whole number. Number of missing items allowed. |
tbl. The input data frame with the summary score appended as a new column.
Computes the max of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
ss_max( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )ss_max( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tribble( ~id, ~session_id, ~A, ~B, ~C, ~D, "id1", "1", 1, 5, 2, NA, "id1", "2", 2, 4, NA, NA, "id1", "3", 3, 3, 3, 3, "id1", "4", 4, 2, 4, 2, "id1", "5", 5, 1, 5, 3 ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D") ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D"), max_na = 1, exclude = c("1") ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D"), max_na = 1, exclude = c("1"), events = c("4") )data <- tibble::tribble( ~id, ~session_id, ~A, ~B, ~C, ~D, "id1", "1", 1, 5, 2, NA, "id1", "2", 2, 4, NA, NA, "id1", "3", 3, 3, 3, 3, "id1", "4", 4, 2, 4, 2, "id1", "5", 5, 1, 5, 3 ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D") ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D"), max_na = 1, exclude = c("1") ) ss_max( data, name = "summary", vars = c("A", "B", "C", "D"), max_na = 1, exclude = c("1"), events = c("4") )
Computes the mean of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
ss_mean( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )ss_mean( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_mean( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )
Computes the mean of strictly positive values for a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
ss_mean_pos( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )ss_mean_pos( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", -1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", -1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_mean_pos( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )
Computes the number of missing items among a set of variables, with the option to exclude certain values (for non-responses like "Don't know" / "Decline to answer"). If all items are NA, the summary score will not be computed (assuming that the questionnaire was not filled out at all).
ss_nm(data, name, vars, exclude = NULL, events = NULL, combine = TRUE)ss_nm(data, name, vars, exclude = NULL, events = NULL, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_nm( name = "nm", vars = c("a", "b", "c", "d", "e"), exclude = c("777", "999") ) data |> ss_nm( name = "nm", vars = c("a", "b", "c", "d", "e"), exclude = c("777", "999"), event = c("ses-00A", "ses-01A") )data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_nm( name = "nm", vars = c("a", "b", "c", "d", "e"), exclude = c("777", "999") ) data |> ss_nm( name = "nm", vars = c("a", "b", "c", "d", "e"), exclude = c("777", "999"), event = c("ses-00A", "ses-01A") )
Computes the pro-rated sum of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values. Also include a second field
ss_prsum( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, as_integer = TRUE, combine = TRUE )ss_prsum( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, as_integer = TRUE, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
as_integer |
logical. Whether to coerce the summary score to an integer,
default is |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tibble( participant_id = c("A", "A", "A", "B", "A", "B", "A"), session_id = c("ses-00A", "ses-01A", "ses-02A", "ses-02A", "ses-03A", "0ses-3A", "ses-04A"), a = c(1, 2, 3, 4, 5, NA, 1), b = c(1, 777, 3, 4, NA, NA, NA), c = c(1, 2, 999, 4, 777, NA, NA), d = c(1, 2, 3, 777, 999, NA, NA), e = c(NA, 2, 3, NA, 5, NA, NA) ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )data <- tibble::tibble( participant_id = c("A", "A", "A", "B", "A", "B", "A"), session_id = c("ses-00A", "ses-01A", "ses-02A", "ses-02A", "ses-03A", "0ses-3A", "ses-04A"), a = c(1, 2, 3, 4, 5, NA, 1), b = c(1, 777, 3, 4, NA, NA, NA), c = c(1, 2, 999, 4, 777, NA, NA), d = c(1, 2, 3, 777, 999, NA, NA), e = c(NA, 2, 3, NA, 5, NA, NA) ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_prsum( name = "score_prorated_sum", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )
Computes the sum of a set of variables, with the option to exclude certain values (for non-responses like "Don't know"/"Decline to answer") and to set a maximum number of missing values.
ss_sum( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, as_integer = TRUE, combine = TRUE )ss_sum( data, name, vars, max_na = NULL, exclude = NULL, events = NULL, as_integer = TRUE, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. The name of the summary score. |
vars |
character vector. The names of the columns to be summarized. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
events |
character (vector). Only compute the summary score for the specified events (Default: NULL; computed for all events). |
as_integer |
logical. Whether to coerce the summary score to an integer,
default is |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
tbl. The input data frame with the summary score appended as a new column.
data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )data <- tibble::tribble( ~session_id, ~a, ~b, ~c, ~d, ~e, "ses-00A", 1, 1, 1, 1, NA, "ses-01A", 2, 777, 2, 2, 2, "ses-02A", 3, 3, 999, 3, 3, "ses-02A", 4, 4, 4, 777, NA, "ses-03A", 5, NA, 777, 999, 5, "ses-03A", NA, NA, NA, NA, NA, "ses-04A", 1, NA, NA, NA, NA ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999") ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = 1, exclude = c("777", "999"), combine = FALSE ) data |> ss_sum( name = "mean", vars = c("a", "b", "c", "d", "e"), max_na = NULL, exclude = NULL, events = c("ses-00A", "ses-01A"), )
This function computes the T-score based on the given columns, and the provided T-score table.
ss_tscore( data, data_norm = NULL, vars, name = "tscore", max_na = NULL, exclude = NULL, col_age = "age", col_sex = "sex", combine = TRUE )ss_tscore( data, data_norm = NULL, vars, name = "tscore", max_na = NULL, exclude = NULL, col_age = "age", col_sex = "sex", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
data_norm |
tbl. Data frame containing the T-score table. See details. |
vars |
character vector. The names of the columns to be summarized. |
name |
character. The column name of the T-score. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: NULL; no restriction on missing values). |
exclude |
character (vector). The value(s) to be excluded (Default: NULL; all values are used). |
col_age |
character. The name of the age column. |
col_sex |
character The name of sex column. |
combine |
logical. Whether to combine the summary score column with the input data frame (Default: TRUE). |
The data_norm should be a data frame containing the T-score table. The
default value NULL is only used for internal usage (see below). For normal
usage, the data_norm should be provided.
The table should have the following columns:
sex: character or factor both ok. The biological sex of the participant.
The values should be either "1" (male) or "2" (female).
age_min: numeric. The minimum age of the participant.
age_max: numeric. The maximum age of the participant.
scale_r: numeric. The raw score of the scale.
scale_t: numeric. The T-score of the scale.
For example
A tibble: n x 5
| sex | age_min | age_max | scale_r | scale_t |
<chr> |
<dbl> |
<dbl> |
<dbl> |
<dbl> |
| 1 | 18 | 35 | 50 | 1 |
| 1 | 18 | 35 | 50.5 | 2 |
| 1 | 18 | 35 | 51 | 3 |
| 1 | 18 | 35 | 51.5 | 4 |
| ... |
If the age of the participant is out of the range of the T-score table,
the function will return NA.
If the raw score is out of the range of the T-score table, the function
will return NA.
If any of the sex column is not "1" or "2",
the function will return NA.
If any of the required columns has NA, that row will return NA.
When used in DSM internally, the data_norm can be omitted. Instead, the
function will try to find the T-score table from the list_tscore option,
and tries to find the tscore list based on object name provided in the
list_tscore option. Once the object is found, the function will automatically
extract the T-score table based on the function name.
The list_tscore object should present in the global environment.
See get_tscore_tbl() for more details on how to construct
the list_tscore.
For example
my_tscore <<- readRDS("aseba_tscore.rds")
options(list_tscore = "my_tscore")
compute_mh_x_yyyy_zz_tscore(data)
tbl. The input data frame with the T-score appended as a new column
if combine is TRUE, otherwise only the T-score column.
data_norm <- tibble::tibble( sex = c("1", "1", "1", "1", "1"), age_min = 18, age_max = 35, scale_r = 0:4, scale_t = 20:24 ) data <- tibble::tibble( var1 = c(0, 1, NA, 1, 2), var2 = c(1, 2, 1, 2, 5), age = c(18, 20, 25, 99, 35), sex = c("1", "1", "1", "1", "1") ) ss_tscore( data = data, data_norm = data_norm, max_na = 0, vars = c("var1", "var2") )data_norm <- tibble::tibble( sex = c("1", "1", "1", "1", "1"), age_min = 18, age_max = 35, scale_r = 0:4, scale_t = 20:24 ) data <- tibble::tibble( var1 = c(0, 1, NA, 1, 2), var2 = c(1, 2, 1, 2, 5), age = c(18, 20, 25, 99, 35), sex = c("1", "1", "1", "1", "1") ) ss_tscore( data = data, data_norm = data_norm, max_na = 0, vars = c("var1", "var2") )
Computes the age (in years) of onset use of a given substance.
Returns NA for the participants with no onset use of the provided
substance reported.
sui_substances compute_su_y_sui__onset_useage(data, name, substance, combine = TRUE)sui_substances compute_su_y_sui__onset_useage(data, name, substance, combine = TRUE)
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance to compute the score for. Must be one of the following values:
|
combine |
logical. Whether to combine the summary score column with the input data frame (Default: 'TRUE“). |
sui_substances is a character vector of substances keywords.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_sui__onset_useage( data = data_sui, name = "su_y_sui__alc__onset_useage", substance = "alc" ) ## End(Not run)## Not run: compute_su_y_sui__onset_useage( data = data_sui, name = "su_y_sui__alc__onset_useage", substance = "alc" ) ## End(Not run)
Computes the length of abstinence in days for a given (set of) substance(s). Optionally, allows to filter by period (detailed and/or estimated); only considering a specified number of days before the TLFB interview; and/or only binge use.
tlfb_substances compute_tlfb_abst( data, name, substance = NULL, period = NULL, days = NULL, binge = NULL )tlfb_substances compute_tlfb_abst( data, name, substance = NULL, period = NULL, days = NULL, binge = NULL )
data |
tibble. A data frame containing the TLFB raw data. |
name |
character. The name of the output column for the computed score. |
substance |
character (vector). The substance(s) to compute the score for. Must be one or several of the following values:
(Default: |
period |
character (vector). The period for which the score is
computed for. Must be one of |
days |
integer. Number of days before the TLFB interview to consider.
(Default: |
binge |
(named list of) numeric. Binge threshold(s) for the
substance(s). If only one value is provided, it is used, independent of the
sex of the participant. If a list is provided, it must contain two named
elements: |
tlfb_substances is a character vector of all substances that can be
reported in the TLFB.
A tibble with the computed score for each participant/event.
## Not run: compute_tlfb_abst( data = data_tlfb, name = "su_y_tlfb__alc__cum_abst", substance = "Alcohol" ) ## End(Not run)## Not run: compute_tlfb_abst( data = data_tlfb, name = "su_y_tlfb__alc__cum_abst", substance = "Alcohol" ) ## End(Not run)
Computes the summary score ab_g_dyn__cohort_edu__cgs
Cohort description: Highest education across caregivers
Summarized variables:
ab_p_demo__edu__slf_001
ab_p_demo__edu__slf_001__v01
ab_p_demo__edu__slf_001__v02
ab_p_demo__edu__prtnr_001
ab_p_demo__edu__prtnr_001__v01
Excluded values:
777
999
vars_ab_g_dyn__cohort_edu__cgs compute_ab_g_dyn__cohort_edu__cgs( data, name = "ab_g_dyn__cohort_edu__cgs", exclude = c("777", "999"), combine = TRUE )vars_ab_g_dyn__cohort_edu__cgs compute_ab_g_dyn__cohort_edu__cgs( data, name = "ab_g_dyn__cohort_edu__cgs", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_edu__cgs.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ab_g_dyn__cohort_income__hhold__6lvl
Cohort description: Household income - 6 levels
Summarized variables:
ab_p_demo__income__hhold_001
ab_p_demo__income__hhold_001__v01
vars_ab_g_dyn__cohort_income__hhold__6lvl compute_ab_g_dyn__cohort_income__hhold__6lvl( data, name = "ab_g_dyn__cohort_income__hhold__6lvl", combine = TRUE )vars_ab_g_dyn__cohort_income__hhold__6lvl compute_ab_g_dyn__cohort_income__hhold__6lvl( data, name = "ab_g_dyn__cohort_income__hhold__6lvl", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_income__hhold__6lvl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ab_g_dyn__cohort_prtnrshp__employ
Cohort description: Caregivers' partnership and employment status
Summarized variables:
ab_p_demo__marital__slf_001
ab_p_demo__prtnr_001
ab_p_demo__empl__slf_001
ab_p_demo__empl__prtnr_001
ab_p_demo__empl__prtnr_001__v01
Excluded values:
777
999
vars_ab_g_dyn__cohort_prtnrshp__employ compute_ab_g_dyn__cohort_prtnrshp__employ( data, name = "ab_g_dyn__cohort_prtnrshp__employ", combine = TRUE )vars_ab_g_dyn__cohort_prtnrshp__employ compute_ab_g_dyn__cohort_prtnrshp__employ( data, name = "ab_g_dyn__cohort_prtnrshp__employ", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a character vector
of all column names used to compute summary score of
ab_g_dyn__cohort_prtnrshp__employ.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ab_g_stc__cohort_ethn
Cohort description: Ethnicity (Hispanic or not Hispanic) [Based on
baseline response; missingness filled in from longitudinal responses]
Summarized variables:
ab_p_demo__ethn_001
ab_p_demo__ethn_001__v01
Excluded values:
777
999
Notes:
Values in ab_p_demo__ethn_001__v01 were recoded:
"0" –> "2",
"2" –> "1"
"3" –> "1"
"4" –> "1"
Values in ab_p_demo__ethn_001 were recoded:
"0" –> "2"
vars_ab_g_stc__cohort_ethn compute_ab_g_stc__cohort_ethn( data, name = "ab_g_stc__cohort_ethn", exclude = c("777", "999"), combine = TRUE )vars_ab_g_stc__cohort_ethn compute_ab_g_stc__cohort_ethn( data, name = "ab_g_stc__cohort_ethn", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
a character vector of all column names
used to compute summary score of ab_g_stc__cohort_ethn.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_g_stc__cohort_ethnrace__leg
Cohort description: Ethno-racial identity (Legacy ABCD variable
reporting 6 levels; Hispanic ethnicity report outweighs any racial
endorements) [Based on baseline response; missingness filled in from
longitudinal responses]
Summarized variables:
ab_p_demo__ethn_001
ab_p_demo__ethn_001__v01
ab_p_demo__race_001___0
ab_p_demo__race_001___10
ab_p_demo__race_001___11
ab_p_demo__race_001___12
ab_p_demo__race_001___13
ab_p_demo__race_001___14
ab_p_demo__race_001___15
ab_p_demo__race_001___16
ab_p_demo__race_001___17
ab_p_demo__race_001___18
ab_p_demo__race_001___19
ab_p_demo__race_001___20
ab_p_demo__race_001___21
ab_p_demo__race_001___22
ab_p_demo__race_001___23
ab_p_demo__race_001___24
ab_p_demo__race_001___25
ab_p_demo__race_001___777
ab_p_demo__race_001___999
ab_p_demo__race_001__v01___999
ab_p_demo__race_001__v01___10
ab_p_demo__race_001__v01___11
ab_p_demo__race_001__v01___12
ab_p_demo__race_001__v01___20
ab_p_demo__race_001__v01___21
ab_p_demo__race_001__v01___22
ab_p_demo__race_001__v01___23
ab_p_demo__race_001__v01___13
ab_p_demo__race_001__v01___14
ab_p_demo__race_001__v01___15
ab_p_demo__race_001__v01___17
ab_p_demo__race_001__v01___18
ab_p_demo__race_001__v01___19
ab_p_demo__race_001__v01___16
ab_p_demo__race_001__v01___24
ab_p_demo__race_001__v01___777
vars_ab_g_stc__cohort_ethnrace__leg compute_ab_g_stc__cohort_ethnrace__leg( data, name = "ab_g_stc__cohort_ethnrace__leg", combine = TRUE )vars_ab_g_stc__cohort_ethnrace__leg compute_ab_g_stc__cohort_ethnrace__leg( data, name = "ab_g_stc__cohort_ethnrace__leg", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a character vector of all column names
used to compute summary score of ab_g_stc__cohort_ethnrace__leg.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_g_stc__cohort_ethnrace__mblack
Cohort description: Ethno-racial identity (8 level aggregation providing
information on Black identity for multiracial endorements) [Based on
baseline response; missingness filled in from longitudinal responses]
Summarized variables:
ab_p_demo__ethn_001
ab_p_demo__ethn_001__v01
ab_p_demo__race_001___0
ab_p_demo__race_001___10
ab_p_demo__race_001___11
ab_p_demo__race_001___12
ab_p_demo__race_001___13
ab_p_demo__race_001___14
ab_p_demo__race_001___15
ab_p_demo__race_001___16
ab_p_demo__race_001___17
ab_p_demo__race_001___18
ab_p_demo__race_001___19
ab_p_demo__race_001___20
ab_p_demo__race_001___21
ab_p_demo__race_001___22
ab_p_demo__race_001___23
ab_p_demo__race_001___24
ab_p_demo__race_001___25
ab_p_demo__race_001___777
ab_p_demo__race_001___999
ab_p_demo__race_001__v01___999
ab_p_demo__race_001__v01___10
ab_p_demo__race_001__v01___11
ab_p_demo__race_001__v01___12
ab_p_demo__race_001__v01___20
ab_p_demo__race_001__v01___21
ab_p_demo__race_001__v01___22
ab_p_demo__race_001__v01___23
ab_p_demo__race_001__v01___13
ab_p_demo__race_001__v01___14
ab_p_demo__race_001__v01___15
ab_p_demo__race_001__v01___17
ab_p_demo__race_001__v01___18
ab_p_demo__race_001__v01___19
ab_p_demo__race_001__v01___16
ab_p_demo__race_001__v01___24
ab_p_demo__race_001__v01___777
vars_ab_g_stc__cohort_ethnrace__mblack compute_ab_g_stc__cohort_ethnrace__mblack( data, name = "ab_g_stc__cohort_ethnrace__mblack", combine = TRUE )vars_ab_g_stc__cohort_ethnrace__mblack compute_ab_g_stc__cohort_ethnrace__mblack( data, name = "ab_g_stc__cohort_ethnrace__mblack", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__mblack.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_g_stc__cohort_ethnrace__meim
Cohort description: Ethno-racial identity (15 level classification from
fc_p_meim_001) [Based on baseline response; missingness filled in from
longitudinal responses]
Summarized variables:
fc_p_meim_001
Excluded values:
777
999
vars_ab_g_stc__cohort_ethnrace__meim compute_ab_g_stc__cohort_ethnrace__meim( data, name = "ab_g_stc__cohort_ethnrace__meim", exclude = c("777", "999"), combine = TRUE )vars_ab_g_stc__cohort_ethnrace__meim compute_ab_g_stc__cohort_ethnrace__meim( data, name = "ab_g_stc__cohort_ethnrace__meim", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical, If |
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__meim.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_g_stc__cohort_ethnrace__mhisp
Cohort description: Ethno-racial identity (8 level aggregation providing
information on ethnicity for multiracial endorements) [Based on baseline
response; missingness filled in from longitudinal responses]
Summarized variables:
ab_p_demo__ethn_001
ab_p_demo__ethn_001__v01
ab_p_demo__race_001___0
ab_p_demo__race_001___10
ab_p_demo__race_001___11
ab_p_demo__race_001___12
ab_p_demo__race_001___13
ab_p_demo__race_001___14
ab_p_demo__race_001___15
ab_p_demo__race_001___16
ab_p_demo__race_001___17
ab_p_demo__race_001___18
ab_p_demo__race_001___19
ab_p_demo__race_001___20
ab_p_demo__race_001___21
ab_p_demo__race_001___22
ab_p_demo__race_001___23
ab_p_demo__race_001___24
ab_p_demo__race_001___25
ab_p_demo__race_001___777
ab_p_demo__race_001___999
ab_p_demo__race_001__v01___999
ab_p_demo__race_001__v01___10
ab_p_demo__race_001__v01___11
ab_p_demo__race_001__v01___12
ab_p_demo__race_001__v01___20
ab_p_demo__race_001__v01___21
ab_p_demo__race_001__v01___22
ab_p_demo__race_001__v01___23
ab_p_demo__race_001__v01___13
ab_p_demo__race_001__v01___14
ab_p_demo__race_001__v01___15
ab_p_demo__race_001__v01___17
ab_p_demo__race_001__v01___18
ab_p_demo__race_001__v01___19
ab_p_demo__race_001__v01___16
ab_p_demo__race_001__v01___24
ab_p_demo__race_001__v01___777
vars_ab_g_stc__cohort_ethnrace__mhisp compute_ab_g_stc__cohort_ethnrace__mhisp( data, name = "ab_g_stc__cohort_ethnrace__mhisp", combine = TRUE )vars_ab_g_stc__cohort_ethnrace__mhisp compute_ab_g_stc__cohort_ethnrace__mhisp( data, name = "ab_g_stc__cohort_ethnrace__mhisp", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a character vector of all
column names used to compute summary score of
ab_g_stc__cohort_ethnrace__mhisp.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_g_stc__cohort_race__nih
Cohort description: Race (NIH classification reporting 7 levels) [Based
on baseline response; missingness filled in from longitudinal responses]
Summarized variables:
ab_p_demo__race_001___0
ab_p_demo__race_001___10
ab_p_demo__race_001___11
ab_p_demo__race_001___12
ab_p_demo__race_001___13
ab_p_demo__race_001___14
ab_p_demo__race_001___15
ab_p_demo__race_001___16
ab_p_demo__race_001___17
ab_p_demo__race_001___18
ab_p_demo__race_001___19
ab_p_demo__race_001___20
ab_p_demo__race_001___21
ab_p_demo__race_001___22
ab_p_demo__race_001___23
ab_p_demo__race_001___24
ab_p_demo__race_001___25
ab_p_demo__race_001___777
ab_p_demo__race_001___999
ab_p_demo__race_001__v01___999
ab_p_demo__race_001__v01___10
ab_p_demo__race_001__v01___11
ab_p_demo__race_001__v01___12
ab_p_demo__race_001__v01___20
ab_p_demo__race_001__v01___21
ab_p_demo__race_001__v01___22
ab_p_demo__race_001__v01___23
ab_p_demo__race_001__v01___13
ab_p_demo__race_001__v01___14
ab_p_demo__race_001__v01___15
ab_p_demo__race_001__v01___17
ab_p_demo__race_001__v01___18
ab_p_demo__race_001__v01___19
ab_p_demo__race_001__v01___16
ab_p_demo__race_001__v01___24
ab_p_demo__race_001__v01___777
vars_ab_g_stc__cohort_race__nih compute_ab_g_stc__cohort_race__nih( data, name = "ab_g_stc__cohort_race__nih", combine = TRUE )vars_ab_g_stc__cohort_race__nih compute_ab_g_stc__cohort_race__nih( data, name = "ab_g_stc__cohort_race__nih", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
a tibble of all column names, baseline and longitudinal,
used to compute summary score of ab_g_stc__cohort_race__nih.
tbl. The input data frame with the summary score appended as
a new column (default). If combine == FALSE, a data frame with two
columns: participant ID and summary score.
Computes the summary score ab_p_demo__ntvam_mean
(Demographics [Parent] (Native American Acculturation): Mean)
Summarized variables:
ab_p_demo__ntvam_005
ab_p_demo__ntvam_006
ab_p_demo__ntvam_007
Excluded values:
999
Validation criterion: maximally 0 of 3 items missing
vars_ab_p_demo__ntvam compute_ab_p_demo__ntvam_mean( data, name = "ab_p_demo__ntvam_mean", max_na = 0, exclude = c("999"), combine = TRUE )vars_ab_p_demo__ntvam compute_ab_p_demo__ntvam_mean( data, name = "ab_p_demo__ntvam_mean", max_na = 0, exclude = c("999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_ab_p_demo__ntvam is a character vector of all column names
used to compute summary score of ab_p_demo__ntvam.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__cohes_mean
(Family Environment Scale [Parent] (Cohesion): Mean)
Summarized variables:
fc_p_fes__cohes_001
fc_p_fes__cohes_002
fc_p_fes__cohes_003
fc_p_fes__cohes_004
fc_p_fes__cohes_005
fc_p_fes__cohes_006
fc_p_fes__cohes_007
fc_p_fes__cohes_008
fc_p_fes__cohes_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__cohes compute_fc_p_fes__cohes_mean( data, name = "fc_p_fes__cohes_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__cohes compute_fc_p_fes__cohes_mean( data, name = "fc_p_fes__cohes_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__cohes is a character vector of all column names
used to compute summary score of fc_p_fes__cohes.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__confl_mean
(Family Environment Scale [Parent] (Conflict): Mean)
Summarized variables:
fc_p_fes__confl_001
fc_p_fes__confl_002
fc_p_fes__confl_003
fc_p_fes__confl_004
fc_p_fes__confl_005
fc_p_fes__confl_006
fc_p_fes__confl_007
fc_p_fes__confl_008
fc_p_fes__confl_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__confl compute_fc_p_fes__confl_mean( data, name = "fc_p_fes__confl_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__confl compute_fc_p_fes__confl_mean( data, name = "fc_p_fes__confl_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__confl is a character vector of all column names
used to compute summary score of fc_p_fes__confl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__expr_mean
(Family Environment Scale [Parent] (Expression): Mean)
Summarized variables:
fc_p_fes__expr_001
fc_p_fes__expr_002
fc_p_fes__expr_003
fc_p_fes__expr_004
fc_p_fes__expr_005
fc_p_fes__expr_006
fc_p_fes__expr_007
fc_p_fes__expr_008
fc_p_fes__expr_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__expr compute_fc_p_fes__expr_mean( data, name = "fc_p_fes__expr_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__expr compute_fc_p_fes__expr_mean( data, name = "fc_p_fes__expr_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__expr is a character vector of all column names
used to compute summary score of fc_p_fes__expr.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__intelcult_mean
(Family Environment Scale [Parent] (Intellectual and cultural): Mean)
Summarized variables:
fc_p_fes__intelcult_001
fc_p_fes__intelcult_002
fc_p_fes__intelcult_003
fc_p_fes__intelcult_004
fc_p_fes__intelcult_005
fc_p_fes__intelcult_006
fc_p_fes__intelcult_007
fc_p_fes__intelcult_008
fc_p_fes__intelcult_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__intelcult compute_fc_p_fes__intelcult_mean( data, name = "fc_p_fes__intelcult_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__intelcult compute_fc_p_fes__intelcult_mean( data, name = "fc_p_fes__intelcult_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__intelcult is a character vector of all column names
used to compute summary score of fc_p_fes__intelcult.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__org_mean
(Family Environment Scale [Parent] (Organization): Mean)
Summarized variables:
fc_p_fes__org_001
fc_p_fes__org_002
fc_p_fes__org_003
fc_p_fes__org_004
fc_p_fes__org_005
fc_p_fes__org_006
fc_p_fes__org_007
fc_p_fes__org_008
fc_p_fes__org_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__org compute_fc_p_fes__org_mean( data, name = "fc_p_fes__org_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__org compute_fc_p_fes__org_mean( data, name = "fc_p_fes__org_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__org is a character vector of all column names
used to compute summary score of fc_p_fes__org.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_fes__rec_mean
(Family Environment Scale [Parent] (Activity and recreational): Mean)
Summarized variables:
fc_p_fes__rec_001
fc_p_fes__rec_002
fc_p_fes__rec_003
fc_p_fes__rec_004
fc_p_fes__rec_005
fc_p_fes__rec_006
fc_p_fes__rec_007
fc_p_fes__rec_008
fc_p_fes__rec_009
Excluded values:
777
999
Validation criterion: maximally 1 of 9 items missing
vars_fc_p_fes__rec compute_fc_p_fes__rec_mean( data, name = "fc_p_fes__rec_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_fes__rec compute_fc_p_fes__rec_mean( data, name = "fc_p_fes__rec_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_fes__rec is a character vector of all column names
used to compute summary score of fc_p_fes__rec.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_meim_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent]: Mean)
Summarized variables:
fc_p_meim__commattach_001
fc_p_meim__commattach_002
fc_p_meim__commattach_003
fc_p_meim__explor_001
fc_p_meim__explor_002
fc_p_meim__explor_003
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_fc_p_meim compute_fc_p_meim_mean( data, name = "fc_p_meim_mean", max_na = 1, combine = TRUE )vars_fc_p_meim compute_fc_p_meim_mean( data, name = "fc_p_meim_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_p_meim is a character vector of all column names
used to compute summary score of fc_p_meim.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_meim__commattach_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Commitment and
attachment): Mean)
Summarized variables:
fc_p_meim__commattach_001
fc_p_meim__commattach_002
fc_p_meim__commattach_003
Excluded values: none
Validation criterion: none of 3 items missing
vars_fc_p_meim__commattach compute_fc_p_meim__commattach_mean( data, name = "fc_p_meim__commattach_mean", max_na = 0, combine = TRUE )vars_fc_p_meim__commattach compute_fc_p_meim__commattach_mean( data, name = "fc_p_meim__commattach_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_p_meim__commattach is a character vector of all column names
used to compute summary score of fc_p_meim__commattach.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_meim__explor_mean
(The Multigroup Ethnic Identity Measure-Revised [Parent] (Exploration): Mean)
Summarized variables:
fc_p_meim__explor_001
fc_p_meim__explor_002
fc_p_meim__explor_003
Excluded values: none
Validation criterion: none of 3 items missing
vars_fc_p_meim__explor compute_fc_p_meim__explor_mean( data, name = "fc_p_meim__explor_mean", max_na = 0, combine = TRUE )vars_fc_p_meim__explor compute_fc_p_meim__explor_mean( data, name = "fc_p_meim__explor_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_p_meim__explor is a character vector of all column names
used to compute summary score of fc_p_meim__explor.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nce_mean
(Neighborhood Collective Efficacy [Parent]: Mean)
Summarized variables:
fc_p_nce__cc_001
fc_p_nce__cc_002
fc_p_nce__cc_003
fc_p_nce__cc_004
fc_p_nce__cc_005
fc_p_nce__isc_001
fc_p_nce__isc_002
fc_p_nce__isc_003
fc_p_nce__isc_004
fc_p_nce__isc_005
Excluded values:
777
Validation criterion: maximally 2 of 10 items missing
Notes:
The following variables are reverse coded before computing the summary score:
fc_p_nce__cc_003
fc_p_nce__cc_004
The value "99" (Don't know) is recoded to "3" (Neither... nor...)
vars_fc_p_nce compute_fc_p_nce_mean(data, name = "fc_p_nce_mean", max_na = 2, combine = TRUE)vars_fc_p_nce compute_fc_p_nce_mean(data, name = "fc_p_nce_mean", max_na = 2, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 2). |
combine |
logical. If |
vars_fc_p_nce is a character vector of all column names
used to compute summary score of fc_p_nce.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nce__cc_mean
(Neighborhood Collective Efficacy [Parent] (Community cohesion): Mean)
Summarized variables:
fc_p_nce__cc_001
fc_p_nce__cc_002
fc_p_nce__cc_003
fc_p_nce__cc_004
fc_p_nce__cc_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
Notes:
The following variables are reverse coded before computing the summary score:
fc_p_nce__cc_003
fc_p_nce__cc_004
The value "99" (Don't know) is recoded to "3" (Neither... nor...)
vars_fc_p_nce__cc compute_fc_p_nce__cc_mean( data, name = "fc_p_nce__cc_mean", max_na = 1, combine = TRUE )vars_fc_p_nce__cc compute_fc_p_nce__cc_mean( data, name = "fc_p_nce__cc_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_p_nce__cc is a character vector of all column names
used to compute summary score of fc_p_nce__cc.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nce__isc_mean
(Neighborhood Collective Efficacy [Parent] (Informal social control): Mean)
Summarized variables:
fc_p_nce__isc_001
fc_p_nce__isc_002
fc_p_nce__isc_003
fc_p_nce__isc_004
fc_p_nce__isc_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
Note: The value "99" (Don't know) is recoded to "3" (Neither... nor...)
vars_fc_p_nce__isc compute_fc_p_nce__isc_mean( data, name = "fc_p_nce__isc_mean", max_na = 1, combine = TRUE )vars_fc_p_nce__isc compute_fc_p_nce__isc_mean( data, name = "fc_p_nce__isc_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_p_nce__isc is a character vector of all column names
used to compute summary score of fc_p_nce__isc.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_nsc__ns_mean
(Neighborhood Safety & Crime [Parent] (Neighborhood safety): Mean)
Summarized variables:
fc_p_nsc__ns_001
fc_p_nsc__ns_002
fc_p_nsc__ns_003
Excluded values:
777
999
Validation criterion: none of 3 items missing
vars_fc_p_nsc__ns compute_fc_p_nsc__ns_mean( data, name = "fc_p_nsc__ns_mean", max_na = 0, combine = TRUE )vars_fc_p_nsc__ns compute_fc_p_nsc__ns_mean( data, name = "fc_p_nsc__ns_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_p_nsc__ns is a character vector of all column names
used to compute summary score of fc_p_nsc__ns.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_pk__knowl_mean
(Parental Knowledge Scale [Parent]: Mean)
Summarized variables:
fc_p_pk__knowl_001
fc_p_pk__knowl_002
fc_p_pk__knowl_003
fc_p_pk__knowl_004
fc_p_pk__knowl_005
fc_p_pk__knowl_006
fc_p_pk__knowl_007
fc_p_pk__knowl_008
fc_p_pk__knowl_009
Excluded values:
777
Validation criterion: maximally 1 of 9 items missing
Notes: All items are reverse coded before computing the summary score.
vars_fc_p_pk__knowl compute_fc_p_pk__knowl_mean( data, name = "fc_p_pk__knowl_mean", max_na = 1, combine = TRUE )vars_fc_p_pk__knowl compute_fc_p_pk__knowl_mean( data, name = "fc_p_pk__knowl_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_p_pk__knowl is a character vector of all column names
used to compute summary score of fc_p_pk__knowl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_psb_mean
(Prosocial Behavior [Parent]: Mean)
Summarized variables:
fc_p_psb_001
fc_p_psb_002
fc_p_psb_003
Excluded values:
777
999
Validation criterion: none of 3 items missing
vars_fc_p_psb compute_fc_p_psb_mean( data, name = "fc_p_psb_mean", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_fc_p_psb compute_fc_p_psb_mean( data, name = "fc_p_psb_mean", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_psb is a character vector of all column names
used to compute summary score of fc_p_psb.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__famil_mean
(Values Scale [Parent] (Familism): Mean (Subscales: supp, ref, obl))
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
fc_p_vs__obl_001
fc_p_vs__obl_002
fc_p_vs__obl_003
fc_p_vs__obl_004
fc_p_vs__obl_005
Excluded values:
777
999
Validation criterion:
maximally 3 of 16 items missing
all sub-scales can be calculated
vars_fc_p_vs__famil compute_fc_p_vs__famil_mean( data, name = "fc_p_vs__famil_mean", max_na = 3, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__famil compute_fc_p_vs__famil_mean( data, name = "fc_p_vs__famil_mean", max_na = 3, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric vector of positive whole number. Number of missing items allowed (Default: 3). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
a character vector of all column names
used to compute summary score of fc_p_vs__famil_mean and
fc_p_vs__famil_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__famil_mean__v01
(Values Scale [Parent] (Familism): Mean - Version 1 (Subscales: supp, ref))
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
Excluded values:
777
999
Validation criterion:
maximally 2 of 11 items missing
all sub-scales can be calculated
vars_fc_p_vs__famil__v01 compute_fc_p_vs__famil_mean__v01( data, name = "fc_p_vs__famil_mean__v01", max_na = 2, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__famil__v01 compute_fc_p_vs__famil_mean__v01( data, name = "fc_p_vs__famil_mean__v01", max_na = 2, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric vector of positive whole number. Number of missing items allowed (Default: 2). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
a character vector of all column names
used to compute summary score of fc_p_vs__famil_mean__v01 and
fc_p_vs__famil_nm__v01.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__indselfrel_mean
(Values Scale [Parent] (Independence and
self-reliance): Mean)
Summarized variables:
fc_p_vs__indselfrel_001
fc_p_vs__indselfrel_002
fc_p_vs__indselfrel_003
fc_p_vs__indselfrel_004
fc_p_vs__indselfrel_005
Excluded values:
777
999
Validation criterion: maximally 1 of 5 items missing
vars_fc_p_vs__indselfrel compute_fc_p_vs__indselfrel_mean( data, name = "fc_p_vs__indselfrel_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__indselfrel compute_fc_p_vs__indselfrel_mean( data, name = "fc_p_vs__indselfrel_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_vs__indselfrel is a character vector of all column names
used to compute summary score of fc_p_vs__indselfrel.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__obl_mean
(Values Scale [Parent] (Family obligation): Mean)
Summarized variables:
fc_p_vs__obl_001
fc_p_vs__obl_002
fc_p_vs__obl_003
fc_p_vs__obl_004
fc_p_vs__obl_005
Excluded values:
777
999
Validation criterion: maximally 1 of 5 items missing
vars_fc_p_vs__obl compute_fc_p_vs__obl_mean( data, name = "fc_p_vs__obl_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__obl compute_fc_p_vs__obl_mean( data, name = "fc_p_vs__obl_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_vs__obl is a character vector of all column names
used to compute summary score of fc_p_vs__obl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__ref_mean
(Values Scale [Parent] (Family as referent): Mean)
Summarized variables:
fc_p_vs__ref_001
fc_p_vs__ref_002
fc_p_vs__ref_003
fc_p_vs__ref_004
fc_p_vs__ref_005
Excluded values:
777
999
Validation criterion: maximally 1 of 5 items missing
vars_fc_p_vs__ref compute_fc_p_vs__ref_mean( data, name = "fc_p_vs__ref_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__ref compute_fc_p_vs__ref_mean( data, name = "fc_p_vs__ref_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_vs__ref is a character vector of all column names
used to compute summary score of fc_p_vs__ref.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__relig_mean
(Values Scale [Parent] (Religion): Mean)
Summarized variables:
fc_p_vs__relig_001
fc_p_vs__relig_002
fc_p_vs__relig_003
fc_p_vs__relig_004
fc_p_vs__relig_005
fc_p_vs__relig_006
fc_p_vs__relig_007
Excluded values:
777
999
Validation criterion: maximally 1 of 7 items missing
vars_fc_p_vs__relig compute_fc_p_vs__relig_mean( data, name = "fc_p_vs__relig_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__relig compute_fc_p_vs__relig_mean( data, name = "fc_p_vs__relig_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_p_vs__relig is a character vector of all column names
used to compute summary score of fc_p_vs__relig.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_p_vs__supp_mean
(Values Scale [Parent] (Family support): Mean)
Summarized variables:
fc_p_vs__supp_001
fc_p_vs__supp_002
fc_p_vs__supp_003
fc_p_vs__supp_004
fc_p_vs__supp_005
fc_p_vs__supp_006
Excluded values:
777
999
Validation criterion: maximally 1 of 6 items missing
vars_fc_p_vs__supp compute_fc_p_vs__supp_mean( data, name = "fc_p_vs__supp_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )vars_fc_p_vs__supp compute_fc_p_vs__supp_mean( data, name = "fc_p_vs__supp_mean", max_na = 1, exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
a character vector of all column names
used to compute summary score of fc_p_vs__supp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_as__safe_mean
(Activity Space [Youth] (Safety): Mean)
Summarized variables:
fc_y_as__safe_001a
fc_y_as__safe_001b
fc_y_as__safe_001c
Excluded values: none
Validation criterion: none of 3 items missing
vars_fc_y_as__safe compute_fc_y_as__safe_mean( data, name = "fc_y_as__safe_mean", max_na = 0, combine = TRUE )vars_fc_y_as__safe compute_fc_y_as__safe_mean( data, name = "fc_y_as__safe_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_y_as__safe is a character vector of all column names
used to compute summary score of fc_y_as__safe.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_crpbi__cg1_mean
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver A):
Mean)
Summarized variables:
fc_y_crpbi__cg1_002
fc_y_crpbi__cg1_003
fc_y_crpbi__cg1_004
fc_y_crpbi__cg1_005
fc_y_crpbi__cg1_006
Excluded values: none
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_crpbi__cg1 compute_fc_y_crpbi__cg1_mean( data, name = "fc_y_crpbi__cg1_mean", max_na = 1, combine = TRUE )vars_fc_y_crpbi__cg1 compute_fc_y_crpbi__cg1_mean( data, name = "fc_y_crpbi__cg1_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_crpbi__cg1 is a character vector of all column names
used to compute summary score of fc_y_crpbi__cg1.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_crpbi__cg2_mean
(Children's Report of Parental Behavioral Inventory [Youth] (Caregiver B):
Mean)
Summarized variables:
fc_y_crpbi__cg2_002
fc_y_crpbi__cg2_003
fc_y_crpbi__cg2_004
fc_y_crpbi__cg2_005
fc_y_crpbi__cg2_006
Excluded values: none
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_crpbi__cg2 compute_fc_y_crpbi__cg2_mean( data, name = "fc_y_crpbi__cg2_mean", max_na = 1, combine = TRUE )vars_fc_y_crpbi__cg2 compute_fc_y_crpbi__cg2_mean( data, name = "fc_y_crpbi__cg2_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_crpbi__cg2 is a character vector of all column names
used to compute summary score of fc_y_crpbi__cg2.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_eut__ethn_mean
(Experiences with Unfair Treatment [Youth] (Ethnicity): Mean)
Summarized variables:
fc_y_eut__ethn_001a
fc_y_eut__ethn_001b
fc_y_eut__ethn_001c/fc_y_eut__ethn_001c__v01
fc_y_eut__ethn_001d (only from event "ses-06A" onwards)
fc_y_eut__ethn_002
fc_y_eut__ethn_003a/fc_y_eut__ethn_003a__v01
fc_y_eut__ethn_003b/fc_y_eut__ethn_003b__v01
fc_y_eut__ethn_003c/fc_y_eut__ethn_003c__v01
Excluded values:
444
777
999
Validation criterion:
before event ses-06A: none of 7 items missing
starting at event ses-06A: maximally 1 of 8 items missing
vars_fc_y_eut__ethn compute_fc_y_eut__ethn_mean(data, name = "fc_y_eut__ethn_mean", combine = TRUE)vars_fc_y_eut__ethn compute_fc_y_eut__ethn_mean(data, name = "fc_y_eut__ethn_mean", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
combine |
logical. If |
vars_fc_y_eut__ethn is a character vector of all column names
used to compute summary score of fc_y_eut__ethn.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_fes__cohes_mean
(Family Environment Scale [Youth] (Cohesion): Mean)
Summarized variables:
fc_y_fes__cohes_001
fc_y_fes__cohes_002
fc_y_fes__cohes_003
fc_y_fes__cohes_004
fc_y_fes__cohes_005
fc_y_fes__cohes_006
fc_y_fes__cohes_007
fc_y_fes__cohes_008
fc_y_fes__cohes_009
Excluded values:
777
Validation criterion: maximally 1 of 9 items missing
vars_fc_y_fes__cohes compute_fc_y_fes__cohes_mean( data, name = "fc_y_fes__cohes_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_fes__cohes compute_fc_y_fes__cohes_mean( data, name = "fc_y_fes__cohes_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_fes__cohes is a character vector of all column names
used to compute summary score of fc_y_fes__cohes.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_fes__confl_mean
(Family Environment Scale [Youth] (Conflict): Mean)
Summarized variables:
fc_y_fes__confl_001
fc_y_fes__confl_002
fc_y_fes__confl_003
fc_y_fes__confl_004
fc_y_fes__confl_005
fc_y_fes__confl_006
fc_y_fes__confl_007
fc_y_fes__confl_008
fc_y_fes__confl_009
Excluded values:
777
Validation criterion: maximally 1 of 9 items missing
vars_fc_y_fes__confl compute_fc_y_fes__confl_mean( data, name = "fc_y_fes__confl_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_fes__confl compute_fc_y_fes__confl_mean( data, name = "fc_y_fes__confl_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_fes__confl is a character vector of all column names
used to compute summary score of fc_y_fes__confl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_lone_mean
(UCLA Loneliness Scale [Youth]: Mean)
Summarized variables:
fc_y_lone_001
fc_y_lone_002
fc_y_lone_003
fc_y_lone_004
fc_y_lone_005
fc_y_lone_006
fc_y_lone_007
Excluded values:
777
999
Validation criterion: maximally 1 of 7 items missing
vars_fc_y_lone compute_fc_y_lone_mean( data, name = "fc_y_lone_mean", max_na = 1, combine = TRUE )vars_fc_y_lone compute_fc_y_lone_mean( data, name = "fc_y_lone_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_lone is a character vector of all column names
used to compute summary score of fc_y_lone.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_meim_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth]: Mean)
Summarized variables:
fc_y_meim__commattach_001
fc_y_meim__commattach_002
fc_y_meim__commattach_003
fc_y_meim__explor_001
fc_y_meim__explor_002
fc_y_meim__explor_003
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_fc_y_meim compute_fc_y_meim_mean( data, name = "fc_y_meim_mean", max_na = 1, combine = TRUE )vars_fc_y_meim compute_fc_y_meim_mean( data, name = "fc_y_meim_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_meim is a character vector of all column names
used to compute summary score of fc_y_meim.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_meim__commattach_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Commitment and
attachment): Mean)
Summarized variables:
fc_y_meim__commattach_001
fc_y_meim__commattach_002
fc_y_meim__commattach_003
Excluded values: none
Validation criterion: none of 3 items missing
vars_fc_y_meim__commattach compute_fc_y_meim__commattach_mean( data, name = "fc_y_meim__commattach_mean", max_na = 0, combine = TRUE )vars_fc_y_meim__commattach compute_fc_y_meim__commattach_mean( data, name = "fc_y_meim__commattach_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_y_meim__commattach is a character vector of all column names
used to compute summary score of fc_y_meim__commattach.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_meim__explor_mean
(The Multigroup Ethnic Identity Measure-Revised [Youth] (Exploration): Mean)
Summarized variables:
fc_y_meim__explor_001
fc_y_meim__explor_002
fc_y_meim__explor_003
Excluded values: none
Validation criterion: none of 3 items missing
vars_fc_y_meim__explor compute_fc_y_meim__explor_mean( data, name = "fc_y_meim__explor_mean", max_na = 0, combine = TRUE )vars_fc_y_meim__explor compute_fc_y_meim__explor_mean( data, name = "fc_y_meim__explor_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_y_meim__explor is a character vector of all column names
used to compute summary score of fc_y_meim__explor.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_mnbs_mean
(Multidimensional Neglectful Behavior Scale [Youth]: Mean)
Summarized variables:
fc_y_mnbs__edusupp_001
fc_y_mnbs__edusupp_002
fc_y_mnbs__edusupp_003
fc_y_mnbs__superv_001
fc_y_mnbs__superv_002
fc_y_mnbs__superv_003
fc_y_mnbs__superv_004
fc_y_mnbs__superv_005
Excluded values:
777
Validation criterion: maximally 1 of 8 items missing
vars_fc_y_mnbs compute_fc_y_mnbs_mean( data, name = "fc_y_mnbs_mean", max_na = 1, combine = TRUE )vars_fc_y_mnbs compute_fc_y_mnbs_mean( data, name = "fc_y_mnbs_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_mnbs is a character vector of all column names
used to compute summary score of fc_y_mnbs.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_mnbs__edusupp_mean
(Multidimensional Neglectful Behavior Scale [Youth] (Education support):
Mean)
Summarized variables:
fc_y_mnbs__edusupp_001
fc_y_mnbs__edusupp_002
fc_y_mnbs__edusupp_003
Excluded values:
777
Validation criterion: none of 3 items missing
vars_fc_y_mnbs__edusupp compute_fc_y_mnbs__edusupp_mean( data, name = "fc_y_mnbs__edusupp_mean", max_na = 0, combine = TRUE )vars_fc_y_mnbs__edusupp compute_fc_y_mnbs__edusupp_mean( data, name = "fc_y_mnbs__edusupp_mean", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If |
vars_fc_y_mnbs__edusupp is a character vector of all column names
used to compute summary score of fc_y_mnbs__edusupp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_mnbs__superv_mean
(Multidimensional Neglectful Behavior Scale [Youth] (Supervision): Mean)
Summarized variables:
fc_y_mnbs__superv_001
fc_y_mnbs__superv_002
fc_y_mnbs__superv_003
fc_y_mnbs__superv_004
fc_y_mnbs__superv_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_mnbs__superv compute_fc_y_mnbs__superv_mean( data, name = "fc_y_mnbs__superv_mean", max_na = 1, combine = TRUE )vars_fc_y_mnbs__superv compute_fc_y_mnbs__superv_mean( data, name = "fc_y_mnbs__superv_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_mnbs__superv is a character vector of all column names
used to compute summary score of fc_y_mnbs__superv.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_naa_mean
(Native American Acculturation [Youth]: Mean)
Summarized variables:
fc_y_naa_001
fc_y_naa_002
fc_y_naa_003
Excluded values:
999
Validation criterion: maximally 0 of 3 items missing
vars_fc_y_naa compute_fc_y_naa_mean( data, name = "fc_y_naa_mean", max_na = 0, exclude = c("999"), combine = TRUE )vars_fc_y_naa compute_fc_y_naa_mean( data, name = "fc_y_naa_mean", max_na = 0, exclude = c("999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_naa is a character vector of all column names
used to compute summary score of fc_y_naa.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_pm_mean
(Parental Monitoring [Youth]: Mean)
Summarized variables:
fc_y_pm_001
fc_y_pm_002
fc_y_pm_003
fc_y_pm_004
fc_y_pm_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_pm compute_fc_y_pm_mean(data, name = "fc_y_pm_mean", max_na = 1, combine = TRUE)vars_fc_y_pm compute_fc_y_pm_mean(data, name = "fc_y_pm_mean", max_na = 1, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_pm is a character vector of all column names
used to compute summary score of fc_y_pm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_pnh_sum
(Peer Network Health [Youth]: Sum)
Summarized variables:
fc_y_pnh_001
fc_y_pnh_002
fc_y_pnh_002__01
fc_y_pnh_003
fc_y_pnh_003__01
Excluded values:
777
Validation criterion: none of 5 items missing
Notes:
fc_y_pnh_001 is scored: No = 0; Yes = 3
fc_y_pnh_002/fc_y_pnh_003 are scored: No = 0; Yes = 2
fc_y_pnh_002__01/fc_y_pnh_003__01 are scored with their original
values (1 through 10)
vars_fc_y_pnh compute_fc_y_pnh_sum( data, name = "fc_y_pnh_sum", max_na = 0, exclude = c("777"), combine = TRUE )vars_fc_y_pnh compute_fc_y_pnh_sum( data, name = "fc_y_pnh_sum", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_pnh is a character vector of all column names
used to compute summary score of fc_y_pnh.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_psb_mean
(Prosocial Behavior [Youth]: Mean)
Summarized variables:
fc_y_psb_001
fc_y_psb_002
fc_y_psb_003
Excluded values:
777
Validation criterion: none of 3 items missing
vars_fc_y_psb compute_fc_y_psb_mean( data, name = "fc_y_psb_mean", max_na = 0, exclude = c("777"), combine = TRUE )vars_fc_y_psb compute_fc_y_psb_mean( data, name = "fc_y_psb_mean", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_psb is a character vector of all column names
used to compute summary score of fc_y_psb.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_rpi_mean
(Resistance to Peer Influence [Youth]: Mean)
Summarized variables:
fc_y_rpi_001
fc_y_rpi_002
fc_y_rpi_003
fc_y_rpi_004
fc_y_rpi_005
fc_y_rpi_006
fc_y_rpi_007
fc_y_rpi_008
fc_y_rpi_009
fc_y_rpi_010
Excluded values: none
Validation criterion: maximally 3 of 10 items missing
Note: The following variables are reverse coded before computing the summary score:
fc_y_rpi_002
fc_y_rpi_006
fc_y_rpi_010
vars_fc_y_rpi compute_fc_y_rpi_mean(data, name = "fc_y_rpi_mean", max_na = 3, combine = TRUE)vars_fc_y_rpi compute_fc_y_rpi_mean(data, name = "fc_y_rpi_mean", max_na = 3, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 3). |
combine |
logical. If |
vars_fc_y_rpi is a character vector of all column names
used to compute summary score of fc_y_rpi.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__dis_mean
(School Risk & Protective Factors [Youth] (School disengagement): Mean)
Summarized variables:
fc_y_srpf__dis_001
fc_y_srpf__dis_002
Excluded values:
777
Validation criterion: none of 2 items missing
vars_fc_y_srpf__dis compute_fc_y_srpf__dis_mean( data, name = "fc_y_srpf__dis_mean", max_na = 0, exclude = c("777"), combine = TRUE )vars_fc_y_srpf__dis compute_fc_y_srpf__dis_mean( data, name = "fc_y_srpf__dis_mean", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_srpf__dis is a character vector of all column names
used to compute summary score of fc_y_srpf__dis.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__env_mean
(School Risk & Protective Factors [Youth] (School environment): Mean)
Summarized variables:
fc_y_srpf__env_001
fc_y_srpf__env_002
fc_y_srpf__env_003
fc_y_srpf__env_004
fc_y_srpf__env_005
fc_y_srpf__env_006
Excluded values:
777
Validation criterion: maximally 1 of 6 items missing
vars_fc_y_srpf__env compute_fc_y_srpf__env_mean( data, name = "fc_y_srpf__env_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_srpf__env compute_fc_y_srpf__env_mean( data, name = "fc_y_srpf__env_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_srpf__env is a character vector of all column names
used to compute summary score of fc_y_srpf__env.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_srpf__involv_mean
(School Risk & Protective Factors [Youth] (School involvement): Mean)
Summarized variables:
fc_y_srpf__involv_001
fc_y_srpf__involv_002
fc_y_srpf__involv_003
fc_y_srpf__involv_004
Excluded values:
777
Validation criterion: none of 4 items missing
vars_fc_y_srpf__involv compute_fc_y_srpf__involv_mean( data, name = "fc_y_srpf__involv_mean", max_na = 0, exclude = c("777"), combine = TRUE )vars_fc_y_srpf__involv compute_fc_y_srpf__involv_mean( data, name = "fc_y_srpf__involv_mean", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_srpf__involv is a character vector of all column names
used to compute summary score of fc_y_srpf__involv.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__famil_mean
(Values Scale [Youth] (Familism): Mean (Subscales: supp, ref, obl))
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
fc_y_vs__obl_001
fc_y_vs__obl_002
fc_y_vs__obl_003
fc_y_vs__obl_004
fc_y_vs__obl_005
Excluded values:
777
Validation criterion:
maximally 3 of 16 items missing
all sub-scales can be calculated
vars_fc_y_vs__famil compute_fc_y_vs__famil_mean( data, name = "fc_y_vs__famil_mean", max_na = 3, exclude = c("777"), combine = TRUE )vars_fc_y_vs__famil compute_fc_y_vs__famil_mean( data, name = "fc_y_vs__famil_mean", max_na = 3, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric vector of positive whole number. Number of missing items allowed (Default: 3). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
a character vector of all column names
used to compute summary score of fc_y_vs__famil_mean and
fc_y_vs__famil_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__famil_mean__v01
(Values Scale [Youth] (Familism): Mean - Version 1 (Subscales: supp, ref))
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
Excluded values:
777
Validation criterion:
maximally 2 of 11 items missing
all sub-scales can be calculated
vars_fc_y_vs__famil__v01 compute_fc_y_vs__famil_mean__v01( data, name = "fc_y_vs__famil_mean__v01", max_na = 2, exclude = c("777"), combine = TRUE )vars_fc_y_vs__famil__v01 compute_fc_y_vs__famil_mean__v01( data, name = "fc_y_vs__famil_mean__v01", max_na = 2, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric vector of positive whole number. Number of missing items allowed (Default: 2). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
a character vector of all column names
used to compute summary score of fc_y_vs__famil_mean__v01 and
fc_y_vs__famil_nm__v01.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__indselfrel_mean
(Values Scale [Youth] (Independence and
self-reliance): Mean)
Summarized variables:
fc_y_vs__indselfrel_001
fc_y_vs__indselfrel_002
fc_y_vs__indselfrel_003
fc_y_vs__indselfrel_004
fc_y_vs__indselfrel_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_vs__indselfrel compute_fc_y_vs__indselfrel_mean( data, name = "fc_y_vs__indselfrel_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_vs__indselfrel compute_fc_y_vs__indselfrel_mean( data, name = "fc_y_vs__indselfrel_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_vs__indselfrel is a character vector of all column names
used to compute summary score of fc_y_vs__indselfrel.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__obl_mean
(Values Scale [Youth] (Family obligation): Mean)
Summarized variables:
fc_y_vs__obl_001
fc_y_vs__obl_002
fc_y_vs__obl_003
fc_y_vs__obl_004
fc_y_vs__obl_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_vs__obl compute_fc_y_vs__obl_mean( data, name = "fc_y_vs__obl_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_vs__obl compute_fc_y_vs__obl_mean( data, name = "fc_y_vs__obl_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_vs__obl is a character vector of all column names
used to compute summary score of fc_y_vs__obl.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__ref_mean
(Values Scale [Youth] (Family as referent): Mean)
Summarized variables:
fc_y_vs__ref_001
fc_y_vs__ref_002
fc_y_vs__ref_003
fc_y_vs__ref_004
fc_y_vs__ref_005
Excluded values:
777
Validation criterion: maximally 1 of 5 items missing
vars_fc_y_vs__ref compute_fc_y_vs__ref_mean( data, name = "fc_y_vs__ref_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_vs__ref compute_fc_y_vs__ref_mean( data, name = "fc_y_vs__ref_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_vs__ref is a character vector of all column names
used to compute summary score of fc_y_vs__ref.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__relig_mean
(Values Scale [Youth] (Religion): Mean)
Summarized variables:
fc_y_vs__relig_001
fc_y_vs__relig_002
fc_y_vs__relig_003
fc_y_vs__relig_004
fc_y_vs__relig_005
fc_y_vs__relig_006
fc_y_vs__relig_007
Excluded values:
777
Validation criterion: maximally 1 of 7 items missing
vars_fc_y_vs__relig compute_fc_y_vs__relig_mean( data, name = "fc_y_vs__relig_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_vs__relig compute_fc_y_vs__relig_mean( data, name = "fc_y_vs__relig_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_vs__relig is a character vector of all column names
used to compute summary score of fc_y_vs__relig.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_vs__supp_mean
(Values Scale [Youth] (Family support): Mean)
Summarized variables:
fc_y_vs__supp_001
fc_y_vs__supp_002
fc_y_vs__supp_003
fc_y_vs__supp_004
fc_y_vs__supp_005
fc_y_vs__supp_006
Excluded values:
777
Validation criterion: maximally 1 of 6 items missing
vars_fc_y_vs__supp compute_fc_y_vs__supp_mean( data, name = "fc_y_vs__supp_mean", max_na = 1, exclude = c("777"), combine = TRUE )vars_fc_y_vs__supp compute_fc_y_vs__supp_mean( data, name = "fc_y_vs__supp_mean", max_na = 1, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_fc_y_vs__supp is a character vector of all column names
used to compute summary score of fc_y_vs__supp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score fc_y_wpss_mean
(Wills Problem Solving Scale [Youth]: Mean)
Summarized variables:
fc_y_wpss_001
fc_y_wpss_002
fc_y_wpss_003
fc_y_wpss_004
fc_y_wpss_005
fc_y_wpss_006
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_fc_y_wpss compute_fc_y_wpss_mean( data, name = "fc_y_wpss_mean", max_na = 1, combine = TRUE )vars_fc_y_wpss compute_fc_y_wpss_mean( data, name = "fc_y_wpss_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score. Default is the name in the description. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If |
vars_fc_y_wpss is a character vector of all column names
used to compute summary score of fc_y_wpss.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_abcl_nm
Adult Behavior Checklist [Parent]: Number missing
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__rule_003
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__som_001
mh_p_abcl__othpr_001
mh_p_abcl__othpr_002
mh_p_abcl__othpr_003
mh_p_abcl__othpr_004
mh_p_abcl__othpr_005
mh_p_abcl__othpr_006
mh_p_abcl__othpr_007
mh_p_abcl__othpr_008
mh_p_abcl__othpr_009
mh_p_abcl__othpr_010
mh_p_abcl__othpr_011
mh_p_abcl__othpr_012
mh_p_abcl__tho_005
mh_p_abcl__tho_007
Excluded values:
777
999
vars_mh_p_abcl compute_mh_p_abcl_nm( data, name = "mh_p_abcl_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl compute_mh_p_abcl_nm( data, name = "mh_p_abcl_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl is vector of all column names
used to compute summary score of mh_p_abcl scores.
tbl. see combine.
## Not run: compute_mh_p_abcl_nm(data) |> select( any_of(c("mh_p_abcl_nm", vars_mh_p_abcl)) ) ## End(Not run)## Not run: compute_mh_p_abcl_nm(data) |> select( any_of(c("mh_p_abcl_nm", vars_mh_p_abcl)) ) ## End(Not run)
Computes the summary score mh_p_abcl__afs__frnd_nm
Adult Behavior Checklist [Parent] (Adaptive Functioning Scale -
Friends): Number missing
Summarized variables:
mh_p_abcl__frnd_001
mh_p_abcl__frnd_002
mh_p_abcl__frnd_003
mh_p_abcl__frnd_004
Excluded values:
777
999
vars_mh_p_abcl__afs__frnd compute_mh_p_abcl__afs__frnd_nm( data, name = "mh_p_abcl__afs__frnd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__afs__frnd compute_mh_p_abcl__afs__frnd_nm( data, name = "mh_p_abcl__afs__frnd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__afs__frnd is vector of all column names
used to compute summary score of mh_p_abcl__afs__frnd scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__afs__frnd_nm(data) |> select( any_of(c("mh_p_abcl__afs__frnd_nm", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__afs__frnd_nm(data) |> select( any_of(c("mh_p_abcl__afs__frnd_nm", vars_mh_p_abcl__afs__frnd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__cg2_sex
Adult Behavior Checklist [Parent] Sex Assignment
Summarized variables:
mh_p_abcl__cg2_001
Excluded values:
777
999
vars_mh_p_abcl__cg2 compute_mh_p_abcl__cg2_sex(data, name = "mh_p_abcl__cg2_sex", combine = TRUE)vars_mh_p_abcl__cg2 compute_mh_p_abcl__cg2_sex(data, name = "mh_p_abcl__cg2_sex", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
vars_mh_p_abcl__cg2 is vector of all column names
used to compute summary score of mh_p_abcl__cg2 scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__cg2_sex(data) |> select( any_of(c("mh_p_abcl__cg2_sex", vars_mh_p_abcl__cg2)) ) ## End(Not run)## Not run: compute_mh_p_abcl__cg2_sex(data) |> select( any_of(c("mh_p_abcl__cg2_sex", vars_mh_p_abcl__cg2)) ) ## End(Not run)
Computes the summary score mh_p_abcl__critic_nm
Adult Behavior Checklist [Parent] (Critical items): Number missing
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__tho_001
mh_p_abcl__othpr__adhd_001
mh_p_abcl__anxdep__dep_001
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__tho__dep_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__tho_002
mh_p_abcl__aggr_001
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_006
mh_p_abcl__rule_002
mh_p_abcl__tho__dep_002
mh_p_abcl__rule__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__anxdep__dep_004
vars_mh_p_abcl__critic compute_mh_p_abcl__critic_nm( data, name = "mh_p_abcl__critic_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__critic compute_mh_p_abcl__critic_nm( data, name = "mh_p_abcl__critic_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__critic is vector of all column names
used to compute summary score of mh_p_abcl__critic scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__critic_nm(data) |> select( any_of(c("mh_p_abcl__critic_nm", vars_mh_p_abcl__critic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__critic_nm(data) |> select( any_of(c("mh_p_abcl__critic_nm", vars_mh_p_abcl__critic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__adhd_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
Number missing
Summarized variables:
mh_p_abcl__aggr__adhd_001
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__othpr__adhd_001
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__rule__adhd_001
Excluded values:
777
999
vars_mh_p_abcl__dsm__adhd compute_mh_p_abcl__dsm__adhd_nm( data, name = "mh_p_abcl__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__adhd compute_mh_p_abcl__dsm__adhd_nm( data, name = "mh_p_abcl__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__adhd is vector of all column names
used to compute summary score of mh_p_abcl__dsm__adhd scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__adhd_nm(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_nm", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__adhd_nm(data) |> select( any_of(c("mh_p_abcl__dsm__adhd_nm", vars_mh_p_abcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__antsoc_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Number missing
Summarized variables:
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__attn__antsoc_001
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
vars_mh_p_abcl__dsm__antsoc compute_mh_p_abcl__dsm__antsoc_nm( data, name = "mh_p_abcl__dsm__antsoc_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__antsoc compute_mh_p_abcl__dsm__antsoc_nm( data, name = "mh_p_abcl__dsm__antsoc_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__antsoc is vector of all column names
used to compute summary score of mh_p_abcl__dsm__antsoc scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__antsoc_nm(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_nm", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__antsoc_nm(data) |> select( any_of(c("mh_p_abcl__dsm__antsoc_nm", vars_mh_p_abcl__dsm__antsoc)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__anx_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety
problems): Number missing
Summarized variables:
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
Excluded values:
777
999
vars_mh_p_abcl__dsm__anx compute_mh_p_abcl__dsm__anx_nm( data, name = "mh_p_abcl__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__anx compute_mh_p_abcl__dsm__anx_nm( data, name = "mh_p_abcl__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__anx is vector of all column names
used to compute summary score of mh_p_abcl__dsm__anx scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__anx_nm(data) |> select( any_of(c("mh_p_abcl__dsm__anx_nm", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__anx_nm(data) |> select( any_of(c("mh_p_abcl__dsm__anx_nm", vars_mh_p_abcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__avoid_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Number missing
Summarized variables:
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__othpr__avoid_001
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
Excluded values:
777
999
vars_mh_p_abcl__dsm__avoid compute_mh_p_abcl__dsm__avoid_nm( data, name = "mh_p_abcl__dsm__avoid_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__avoid compute_mh_p_abcl__dsm__avoid_nm( data, name = "mh_p_abcl__dsm__avoid_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__avoid is vector of all column names
used to compute summary score of mh_p_abcl__dsm__avoid scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__avoid_nm(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_nm", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__avoid_nm(data) |> select( any_of(c("mh_p_abcl__dsm__avoid_nm", vars_mh_p_abcl__dsm__avoid)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__dep_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Number missing
Summarized variables:
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
mh_p_abcl__som__dep_001
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
vars_mh_p_abcl__dsm__dep compute_mh_p_abcl__dsm__dep_nm( data, name = "mh_p_abcl__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__dep compute_mh_p_abcl__dsm__dep_nm( data, name = "mh_p_abcl__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__dep is vector of all column names
used to compute summary score of mh_p_abcl__dsm__dep scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__dep_nm(data) |> select( any_of(c("mh_p_abcl__dsm__dep_nm", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__dep_nm(data) |> select( any_of(c("mh_p_abcl__dsm__dep_nm", vars_mh_p_abcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__dsm__somat_nm
Adult Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
Summarized variables:
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
vars_mh_p_abcl__dsm__somat compute_mh_p_abcl__dsm__somat_nm( data, name = "mh_p_abcl__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__dsm__somat compute_mh_p_abcl__dsm__somat_nm( data, name = "mh_p_abcl__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__dsm__somat is vector of all column names
used to compute summary score of mh_p_abcl__dsm__somat scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__dsm__somat_nm(data) |> select( any_of(c("mh_p_abcl__dsm__somat_nm", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_abcl__dsm__somat_nm(data) |> select( any_of(c("mh_p_abcl__dsm__somat_nm", vars_mh_p_abcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su_nm
Adult Behavior Checklist [Parent] (Substance use): Number missing
Summarized variables:
mh_p_abcl__drg_001
mh_p_abcl__drunk_001
mh_p_abcl__nic_001
Excluded values:
777
999
vars_mh_p_abcl__su compute_mh_p_abcl__su_nm( data, name = "mh_p_abcl__su_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__su compute_mh_p_abcl__su_nm( data, name = "mh_p_abcl__su_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__su is vector of all column names
used to compute summary score of mh_p_abcl__su scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__su_nm(data) |> select( any_of(c("mh_p_abcl__su_nm", vars_mh_p_abcl__su)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su_nm(data) |> select( any_of(c("mh_p_abcl__su_nm", vars_mh_p_abcl__su)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drg_nm
Adult Behavior Checklist [Parent] (Days drug use): Number missing
Summarized variables:
mh_p_abcl__drg_001
Excluded values:
777
999
vars_mh_p_abcl__su__drg compute_mh_p_abcl__su__drg_nm( data, name = "mh_p_abcl__su__drg_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__su__drg compute_mh_p_abcl__su__drg_nm( data, name = "mh_p_abcl__su__drg_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__su__drg is vector of all column names
used to compute summary score of mh_p_abcl__su__drg scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__su__drg_nm(data) |> select( any_of(c("mh_p_abcl__su__drg_nm", vars_mh_p_abcl__su__drg)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drg_nm(data) |> select( any_of(c("mh_p_abcl__su__drg_nm", vars_mh_p_abcl__su__drg)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__drunk_nm
Adult Behavior Checklist [Parent] (Days Drunk): Number missing
Summarized variables:
mh_p_abcl__drunk_001
Excluded values:
777
999
vars_mh_p_abcl__su__drunk compute_mh_p_abcl__su__drunk_nm( data, name = "mh_p_abcl__su__drunk_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__su__drunk compute_mh_p_abcl__su__drunk_nm( data, name = "mh_p_abcl__su__drunk_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__su__drunk is vector of all column names
used to compute summary score of mh_p_abcl__su__drunk scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__su__drunk_nm(data) |> select( any_of(c("mh_p_abcl__su__drunk_nm", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__drunk_nm(data) |> select( any_of(c("mh_p_abcl__su__drunk_nm", vars_mh_p_abcl__su__drunk)) ) ## End(Not run)
Computes the summary score mh_p_abcl__su__nic_nm
Adult Behavior Checklist [Parent] (Tobacco per day): Number missing
Summarized variables:
mh_p_abcl__nic_001
Excluded values:
777
999
vars_mh_p_abcl__su__nic compute_mh_p_abcl__su__nic_nm( data, name = "mh_p_abcl__su__nic_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__su__nic compute_mh_p_abcl__su__nic_nm( data, name = "mh_p_abcl__su__nic_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__su__nic is vector of all column names
used to compute summary score of mh_p_abcl__su__nic scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__su__nic_nm(data) |> select( any_of(c("mh_p_abcl__su__nic_nm", vars_mh_p_abcl__su__nic)) ) ## End(Not run)## Not run: compute_mh_p_abcl__su__nic_nm(data) |> select( any_of(c("mh_p_abcl__su__nic_nm", vars_mh_p_abcl__su__nic)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__aggr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Number missing
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
Excluded values:
777
999
vars_mh_p_abcl__synd__aggr compute_mh_p_abcl__synd__aggr_nm( data, name = "mh_p_abcl__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__aggr compute_mh_p_abcl__synd__aggr_nm( data, name = "mh_p_abcl__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__aggr is vector of all column names
used to compute summary score of mh_p_abcl__synd__aggr scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__aggr_nm(data) |> select( any_of(c("mh_p_abcl__synd__aggr_nm", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__aggr_nm(data) |> select( any_of(c("mh_p_abcl__synd__aggr_nm", vars_mh_p_abcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__anxdep_nm
Adult Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Number missing
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
Excluded values:
777
999
vars_mh_p_abcl__synd__anxdep compute_mh_p_abcl__synd__anxdep_nm( data, name = "mh_p_abcl__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__anxdep compute_mh_p_abcl__synd__anxdep_nm( data, name = "mh_p_abcl__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__anxdep is vector of all column names
used to compute summary score of mh_p_abcl__synd__anxdep scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__anxdep_nm(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_nm", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__anxdep_nm(data) |> select( any_of(c("mh_p_abcl__synd__anxdep_nm", vars_mh_p_abcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__attn_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Number missing
Summarized variables:
mh_p_abcl__attn_001
mh_p_abcl__attn_002
mh_p_abcl__attn_003
mh_p_abcl__attn_004
mh_p_abcl__attn_005
mh_p_abcl__attn_006
mh_p_abcl__attn__adhd_001
mh_p_abcl__attn__adhd_002
mh_p_abcl__attn__adhd_003
mh_p_abcl__attn__adhd_004
mh_p_abcl__attn__adhd_005
mh_p_abcl__attn__adhd_006
mh_p_abcl__attn__adhd_007
mh_p_abcl__attn__antsoc_001
mh_p_abcl__attn__dep_001
mh_p_abcl__attn__dep_002
mh_p_abcl__attn__dep_003
Excluded values:
777
999
vars_mh_p_abcl__synd__attn compute_mh_p_abcl__synd__attn_nm( data, name = "mh_p_abcl__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__attn compute_mh_p_abcl__synd__attn_nm( data, name = "mh_p_abcl__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__attn is vector of all column names
used to compute summary score of mh_p_abcl__synd__attn scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__attn_nm(data) |> select( any_of(c("mh_p_abcl__synd__attn_nm", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__attn_nm(data) |> select( any_of(c("mh_p_abcl__synd__attn_nm", vars_mh_p_abcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__ext_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - External): Number
missing
Summarized variables:
mh_p_abcl__aggr_001
mh_p_abcl__aggr_002
mh_p_abcl__aggr_003
mh_p_abcl__aggr_004
mh_p_abcl__aggr_005
mh_p_abcl__aggr_006
mh_p_abcl__aggr_007
mh_p_abcl__aggr__adhd_001
mh_p_abcl__aggr__antsoc_001
mh_p_abcl__aggr__antsoc_002
mh_p_abcl__aggr__antsoc_003
mh_p_abcl__aggr__antsoc_004
mh_p_abcl__aggr__antsoc_005
mh_p_abcl__aggr__antsoc_006
mh_p_abcl__aggr__antsoc_007
mh_p_abcl__aggr__antsoc_008
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
vars_mh_p_abcl__synd__ext compute_mh_p_abcl__synd__ext_nm( data, name = "mh_p_abcl__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__ext compute_mh_p_abcl__synd__ext_nm( data, name = "mh_p_abcl__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__ext is vector of all column names
used to compute summary score of mh_p_abcl__synd__ext scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__ext_nm(data) |> select( any_of(c("mh_p_abcl__synd__ext_nm", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__ext_nm(data) |> select( any_of(c("mh_p_abcl__synd__ext_nm", vars_mh_p_abcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__int_nm
Adult Behavior Checklist [Parent] (Internalizing): Number missing
Summarized variables:
mh_p_abcl__anxdep_001
mh_p_abcl__anxdep_002
mh_p_abcl__anxdep_003
mh_p_abcl__anxdep_004
mh_p_abcl__anxdep__anx_001
mh_p_abcl__anxdep__anx_002
mh_p_abcl__anxdep__anx_003
mh_p_abcl__anxdep__avoid_001
mh_p_abcl__anxdep__avoid_002
mh_p_abcl__anxdep__dep_001
mh_p_abcl__anxdep__dep_002
mh_p_abcl__anxdep__dep_003
mh_p_abcl__anxdep__dep_004
mh_p_abcl__anxdep__dep_005
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
vars_mh_p_abcl__synd__int compute_mh_p_abcl__synd__int_nm( data, name = "mh_p_abcl__synd__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__int compute_mh_p_abcl__synd__int_nm( data, name = "mh_p_abcl__synd__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__int is vector of all column names
used to compute summary score of mh_p_abcl__synd__int scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__int_nm(data) |> select( any_of(c("mh_p_abcl__synd__int_nm", vars_mh_p_abcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__int_nm(data) |> select( any_of(c("mh_p_abcl__synd__int_nm", vars_mh_p_abcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__intru_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Intrusive): Number
missing
Summarized variables:
mh_p_abcl__intru_001
mh_p_abcl__intru_002
mh_p_abcl__intru_003
mh_p_abcl__intru_004
mh_p_abcl__intru_005
mh_p_abcl__intru_006
Excluded values:
777
999
vars_mh_p_abcl__synd__intru compute_mh_p_abcl__synd__intru_nm( data, name = "mh_p_abcl__synd__intru_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__intru compute_mh_p_abcl__synd__intru_nm( data, name = "mh_p_abcl__synd__intru_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__intru is vector of all column names
used to compute summary score of mh_p_abcl__synd__intru scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__intru_nm(data) |> select( any_of(c("mh_p_abcl__synd__intru_nm", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__intru_nm(data) |> select( any_of(c("mh_p_abcl__synd__intru_nm", vars_mh_p_abcl__synd__intru)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__othpr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Number missing
Summarized variables:
mh_p_abcl__othpr_001
mh_p_abcl__othpr_002
mh_p_abcl__othpr_003
mh_p_abcl__othpr_004
mh_p_abcl__othpr_005
mh_p_abcl__othpr_006
mh_p_abcl__othpr_007
mh_p_abcl__othpr_008
mh_p_abcl__othpr_009
mh_p_abcl__othpr_010
mh_p_abcl__othpr_011
mh_p_abcl__othpr_012
mh_p_abcl__othpr__adhd_001
mh_p_abcl__othpr__adhd_002
mh_p_abcl__othpr__adhd_003
mh_p_abcl__othpr__adhd_004
mh_p_abcl__othpr__antsoc_001
mh_p_abcl__othpr__antsoc_002
mh_p_abcl__othpr__anx_001
mh_p_abcl__othpr__anx_002
mh_p_abcl__othpr__anx_003
mh_p_abcl__othpr__avoid_001
mh_p_abcl__othpr__dep_001
mh_p_abcl__othpr__dep_002
mh_p_abcl__othpr__dep_003
Excluded values:
777
999
vars_mh_p_abcl__synd__othpr compute_mh_p_abcl__synd__othpr_nm( data, name = "mh_p_abcl__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__othpr compute_mh_p_abcl__synd__othpr_nm( data, name = "mh_p_abcl__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__othpr is vector of all column names
used to compute summary score of mh_p_abcl__synd__othpr scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__othpr_nm(data) |> select( any_of(c("mh_p_abcl__synd__othpr_nm", vars_mh_p_abcl__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__othpr_nm(data) |> select( any_of(c("mh_p_abcl__synd__othpr_nm", vars_mh_p_abcl__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__rule_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Number missing
Summarized variables:
mh_p_abcl__rule_001
mh_p_abcl__rule_002
mh_p_abcl__rule_003
mh_p_abcl__rule__adhd_001
mh_p_abcl__rule__antsoc_001
mh_p_abcl__rule__antsoc_002
mh_p_abcl__rule__antsoc_003
mh_p_abcl__rule__antsoc_004
mh_p_abcl__rule__antsoc_005
mh_p_abcl__rule__antsoc_006
mh_p_abcl__rule__antsoc_007
mh_p_abcl__rule__antsoc_008
mh_p_abcl__rule__antsoc_009
Excluded values:
777
999
vars_mh_p_abcl__synd__rule compute_mh_p_abcl__synd__rule_nm( data, name = "mh_p_abcl__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__rule compute_mh_p_abcl__synd__rule_nm( data, name = "mh_p_abcl__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__rule is vector of all column names
used to compute summary score of mh_p_abcl__synd__rule scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__rule_nm(data) |> select( any_of(c("mh_p_abcl__synd__rule_nm", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__rule_nm(data) |> select( any_of(c("mh_p_abcl__synd__rule_nm", vars_mh_p_abcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__som_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Number missing
Summarized variables:
mh_p_abcl__som_001
mh_p_abcl__som__dep_001
mh_p_abcl__som__somat_001
mh_p_abcl__som__somat_002
mh_p_abcl__som__somat_003
mh_p_abcl__som__somat_004
mh_p_abcl__som__somat_005
mh_p_abcl__som__somat_006
mh_p_abcl__som__somat_007
Excluded values:
777
999
vars_mh_p_abcl__synd__som compute_mh_p_abcl__synd__som_nm( data, name = "mh_p_abcl__synd__som_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__som compute_mh_p_abcl__synd__som_nm( data, name = "mh_p_abcl__synd__som_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__som is vector of all column names
used to compute summary score of mh_p_abcl__synd__som scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__som_nm(data) |> select( any_of(c("mh_p_abcl__synd__som_nm", vars_mh_p_abcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__som_nm(data) |> select( any_of(c("mh_p_abcl__synd__som_nm", vars_mh_p_abcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__tho_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Number missing
Summarized variables:
mh_p_abcl__tho_001
mh_p_abcl__tho_002
mh_p_abcl__tho_003
mh_p_abcl__tho_004
mh_p_abcl__tho_005
mh_p_abcl__tho_006
mh_p_abcl__tho_007
mh_p_abcl__tho__dep_001
mh_p_abcl__tho__dep_002
Excluded values:
777
999
vars_mh_p_abcl__synd__tho compute_mh_p_abcl__synd__tho_nm( data, name = "mh_p_abcl__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__tho compute_mh_p_abcl__synd__tho_nm( data, name = "mh_p_abcl__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__tho is vector of all column names
used to compute summary score of mh_p_abcl__synd__tho scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__tho_nm(data) |> select( any_of(c("mh_p_abcl__synd__tho_nm", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__tho_nm(data) |> select( any_of(c("mh_p_abcl__synd__tho_nm", vars_mh_p_abcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_abcl__synd__wthdr_nm
Adult Behavior Checklist [Parent] (Syndrome Scale - Withdrawn): Number
missing
Summarized variables:
mh_p_abcl__wthdr_001
mh_p_abcl__wthdr_002
mh_p_abcl__wthdr_003
mh_p_abcl__wthdr_004
mh_p_abcl__wthdr__avoid_001
mh_p_abcl__wthdr__avoid_002
mh_p_abcl__wthdr__avoid_003
mh_p_abcl__wthdr__avoid_004
mh_p_abcl__wthdr__dep_001
Excluded values:
777
999
vars_mh_p_abcl__synd__wthdr compute_mh_p_abcl__synd__wthdr_nm( data, name = "mh_p_abcl__synd__wthdr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_abcl__synd__wthdr compute_mh_p_abcl__synd__wthdr_nm( data, name = "mh_p_abcl__synd__wthdr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_abcl__synd__wthdr is vector of all column names
used to compute summary score of mh_p_abcl__synd__wthdr scores.
tbl. see combine.
## Not run: compute_mh_p_abcl__synd__wthdr_nm(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_nm", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)## Not run: compute_mh_p_abcl__synd__wthdr_nm(data) |> select( any_of(c("mh_p_abcl__synd__wthdr_nm", vars_mh_p_abcl__synd__wthdr)) ) ## End(Not run)
Computes the summary score mh_p_asr_nm
Adult Self Report [Parent]: Number missing
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_008
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__attn__inatt_002
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__rule_001
mh_p_asr__rule_003
mh_p_asr__rule__antsoc_007
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho__dep_001
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_007
mh_p_asr__attn__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__othpr__avoid_001
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_006
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__wthdr__dep_001
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__attn_001
mh_p_asr__attn_002
mh_p_asr__attn_003
mh_p_asr__attn_004
mh_p_asr__attn_005
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
mh_p_asr__rule_002
mh_p_asr__rule_004
mh_p_asr__som_001
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__othpr_001
mh_p_asr__othpr_002
mh_p_asr__othpr_003
mh_p_asr__othpr_004
mh_p_asr__othpr_005
mh_p_asr__othpr_006
mh_p_asr__othpr_007
mh_p_asr__othpr_008
mh_p_asr__othpr_009
mh_p_asr__othpr_010
mh_p_asr__othpr_011
mh_p_asr__tho_003
mh_p_asr__tho_004
mh_p_asr__tho_008
Excluded values:
777
999
vars_mh_p_asr compute_mh_p_asr_nm( data, name = "mh_p_asr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr compute_mh_p_asr_nm( data, name = "mh_p_asr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr is vector of all column names
used to compute summary score of mh_p_asr scores.
tbl. see combine.
## Not run: compute_mh_p_asr_nm(data) |> select( any_of(c("mh_p_asr_nm", vars_mh_p_asr)) ) ## End(Not run)## Not run: compute_mh_p_asr_nm(data) |> select( any_of(c("mh_p_asr_nm", vars_mh_p_asr)) ) ## End(Not run)
Computes the summary score mh_p_asr__afs__strng_nm
Adult Self Report [Parent] (Adaptive Functioning Scale - Personal
strength): Number missing
Summarized variables:
mh_p_asr__strng_001
mh_p_asr__strng_002
mh_p_asr__strng_003
mh_p_asr__strng_004
mh_p_asr__strng_005
mh_p_asr__strng_006
mh_p_asr__strng_007
mh_p_asr__strng_008
mh_p_asr__strng_009
mh_p_asr__strng_010
mh_p_asr__strng_011
Excluded values:
777
999
vars_mh_p_asr__afs__strng compute_mh_p_asr__afs__strng_nm( data, name = "mh_p_asr__afs__strng_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__afs__strng compute_mh_p_asr__afs__strng_nm( data, name = "mh_p_asr__afs__strng_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__afs__strng is vector of all column names
used to compute summary score of mh_p_asr__afs__strng scores.
tbl. see combine.
## Not run: compute_mh_p_asr__afs__strng_nm(data) |> select( any_of(c("mh_p_asr__afs__strng_nm", vars_mh_p_asr__afs__strng)) ) ## End(Not run)## Not run: compute_mh_p_asr__afs__strng_nm(data) |> select( any_of(c("mh_p_asr__afs__strng_nm", vars_mh_p_asr__afs__strng)) ) ## End(Not run)
Computes the summary score mh_p_asr__critic_nm
Adult Self Report [Parent] (Critical Items): Number missing
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_008
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__attn__inatt_002
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__rule_001
mh_p_asr__rule_003
mh_p_asr__rule__antsoc_007
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho__dep_001
Excluded values:
777
999
vars_mh_p_asr__critic compute_mh_p_asr__critic_nm( data, name = "mh_p_asr__critic_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__critic compute_mh_p_asr__critic_nm( data, name = "mh_p_asr__critic_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__critic is vector of all column names
used to compute summary score of mh_p_asr__critic scores.
tbl. see combine.
## Not run: compute_mh_p_asr__critic_nm(data) |> select( any_of(c("mh_p_asr__critic_nm", vars_mh_p_asr__critic)) ) ## End(Not run)## Not run: compute_mh_p_asr__critic_nm(data) |> select( any_of(c("mh_p_asr__critic_nm", vars_mh_p_asr__critic)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD): Number
missing
Summarized variables:
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
Excluded values:
777
999
vars_mh_p_asr__dsm__adhd compute_mh_p_asr__dsm__adhd_nm( data, name = "mh_p_asr__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__adhd compute_mh_p_asr__dsm__adhd_nm( data, name = "mh_p_asr__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__adhd is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__adhd_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd_nm", vars_mh_p_asr__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd_nm", vars_mh_p_asr__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd__hypimp_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD
Hyperactivity-Impulsivity): Number missing
Summarized variables:
mh_p_asr__aggr__hypimp_001
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__rule__hypimp_001
mh_p_asr__tho__hypimp_001
Excluded values:
777
999
vars_mh_p_asr__dsm__adhd__hypimp compute_mh_p_asr__dsm__adhd__hypimp_nm( data, name = "mh_p_asr__dsm__adhd__hypimp_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__adhd__hypimp compute_mh_p_asr__dsm__adhd__hypimp_nm( data, name = "mh_p_asr__dsm__adhd__hypimp_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__adhd__hypimp is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd__hypimp scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__adhd__hypimp_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd__hypimp_nm", vars_mh_p_asr__dsm__adhd__hypimp)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd__hypimp_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd__hypimp_nm", vars_mh_p_asr__dsm__adhd__hypimp)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__adhd__inatt_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - ADHD Inattention):
Number missing
Summarized variables:
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
Excluded values:
777
999
vars_mh_p_asr__dsm__adhd__inatt compute_mh_p_asr__dsm__adhd__inatt_nm( data, name = "mh_p_asr__dsm__adhd__inatt_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__adhd__inatt compute_mh_p_asr__dsm__adhd__inatt_nm( data, name = "mh_p_asr__dsm__adhd__inatt_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__adhd__inatt is vector of all column names
used to compute summary score of mh_p_asr__dsm__adhd__inatt scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__adhd__inatt_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd__inatt_nm", vars_mh_p_asr__dsm__adhd__inatt)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__adhd__inatt_nm(data) |> select( any_of(c("mh_p_asr__dsm__adhd__inatt_nm", vars_mh_p_asr__dsm__adhd__inatt)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__antsoc_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Antisocial
personality problems): Number missing
Summarized variables:
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
mh_p_asr__attn__antsoc_001
mh_p_asr__othpr__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
Excluded values:
777
999
vars_mh_p_asr__dsm__antsoc compute_mh_p_asr__dsm__antsoc_nm( data, name = "mh_p_asr__dsm__antsoc_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__antsoc compute_mh_p_asr__dsm__antsoc_nm( data, name = "mh_p_asr__dsm__antsoc_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__antsoc is vector of all column names
used to compute summary score of mh_p_asr__dsm__antsoc scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__antsoc_nm(data) |> select( any_of(c("mh_p_asr__dsm__antsoc_nm", vars_mh_p_asr__dsm__antsoc)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__antsoc_nm(data) |> select( any_of(c("mh_p_asr__dsm__antsoc_nm", vars_mh_p_asr__dsm__antsoc)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__anx_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Anxiety problems):
Number missing
Summarized variables:
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
Excluded values:
777
999
vars_mh_p_asr__dsm__anx compute_mh_p_asr__dsm__anx_nm( data, name = "mh_p_asr__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__anx compute_mh_p_asr__dsm__anx_nm( data, name = "mh_p_asr__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__anx is vector of all column names
used to compute summary score of mh_p_asr__dsm__anx scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__anx_nm(data) |> select( any_of(c("mh_p_asr__dsm__anx_nm", vars_mh_p_asr__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__anx_nm(data) |> select( any_of(c("mh_p_asr__dsm__anx_nm", vars_mh_p_asr__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__avoid_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Avoidant
personality problems): Number missing
Summarized variables:
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__othpr__avoid_001
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
Excluded values:
777
999
vars_mh_p_asr__dsm__avoid compute_mh_p_asr__dsm__avoid_nm( data, name = "mh_p_asr__dsm__avoid_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__avoid compute_mh_p_asr__dsm__avoid_nm( data, name = "mh_p_asr__dsm__avoid_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__avoid is vector of all column names
used to compute summary score of mh_p_asr__dsm__avoid scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__avoid_nm(data) |> select( any_of(c("mh_p_asr__dsm__avoid_nm", vars_mh_p_asr__dsm__avoid)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__avoid_nm(data) |> select( any_of(c("mh_p_asr__dsm__avoid_nm", vars_mh_p_asr__dsm__avoid)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__dep_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Depresssive
problems): Number missing
Summarized variables:
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__tho__dep_001
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
vars_mh_p_asr__dsm__dep compute_mh_p_asr__dsm__dep_nm( data, name = "mh_p_asr__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__dep compute_mh_p_asr__dsm__dep_nm( data, name = "mh_p_asr__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__dep is vector of all column names
used to compute summary score of mh_p_asr__dsm__dep scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__dep_nm(data) |> select( any_of(c("mh_p_asr__dsm__dep_nm", vars_mh_p_asr__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__dep_nm(data) |> select( any_of(c("mh_p_asr__dsm__dep_nm", vars_mh_p_asr__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_asr__dsm__somat_nm
Adult Self Report [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
Summarized variables:
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
Excluded values:
777
999
vars_mh_p_asr__dsm__somat compute_mh_p_asr__dsm__somat_nm( data, name = "mh_p_asr__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__dsm__somat compute_mh_p_asr__dsm__somat_nm( data, name = "mh_p_asr__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__dsm__somat is vector of all column names
used to compute summary score of mh_p_asr__dsm__somat scores.
tbl. see combine.
## Not run: compute_mh_p_asr__dsm__somat_nm(data) |> select( any_of(c("mh_p_asr__dsm__somat_nm", vars_mh_p_asr__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_asr__dsm__somat_nm(data) |> select( any_of(c("mh_p_asr__dsm__somat_nm", vars_mh_p_asr__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__aggr_nm
Adult Self Report [Parent] (Syndrome Scale - Aggressive Behavior):
Number missing
Summarized variables:
mh_p_asr__aggr_001
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__aggr__hypimp_001
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
Excluded values:
777
999
vars_mh_p_asr__synd__aggr compute_mh_p_asr__synd__aggr_nm( data, name = "mh_p_asr__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__aggr compute_mh_p_asr__synd__aggr_nm( data, name = "mh_p_asr__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__aggr is vector of all column names
used to compute summary score of mh_p_asr__synd__aggr scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__aggr_nm(data) |> select( any_of(c("mh_p_asr__synd__aggr_nm", vars_mh_p_asr__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__aggr_nm(data) |> select( any_of(c("mh_p_asr__synd__aggr_nm", vars_mh_p_asr__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__anxdep_nm
Adult Self Report [Parent] (Syndrome Scale - Anxious/Depressed):
Number missing
Summarized variables:
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
Excluded values:
777
999
vars_mh_p_asr__synd__anxdep compute_mh_p_asr__synd__anxdep_nm( data, name = "mh_p_asr__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__anxdep compute_mh_p_asr__synd__anxdep_nm( data, name = "mh_p_asr__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__anxdep is vector of all column names
used to compute summary score of mh_p_asr__synd__anxdep scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__anxdep_nm(data) |> select( any_of(c("mh_p_asr__synd__anxdep_nm", vars_mh_p_asr__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__anxdep_nm(data) |> select( any_of(c("mh_p_asr__synd__anxdep_nm", vars_mh_p_asr__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__attn_nm
Adult Self Report [Parent] (Syndrome Scale - Attention problems):
Number missing
Summarized variables:
mh_p_asr__attn_001
mh_p_asr__attn_002
mh_p_asr__attn_003
mh_p_asr__attn_004
mh_p_asr__attn_005
mh_p_asr__attn__inatt_001
mh_p_asr__attn__inatt_002
mh_p_asr__attn__inatt_003
mh_p_asr__attn__inatt_004
mh_p_asr__attn__inatt_005
mh_p_asr__attn__inatt_006
mh_p_asr__attn__inatt_007
mh_p_asr__attn__antsoc_001
mh_p_asr__attn__dep_001
mh_p_asr__attn__dep_002
Excluded values:
777
999
vars_mh_p_asr__synd__attn compute_mh_p_asr__synd__attn_nm( data, name = "mh_p_asr__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__attn compute_mh_p_asr__synd__attn_nm( data, name = "mh_p_asr__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__attn is vector of all column names
used to compute summary score of mh_p_asr__synd__attn scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__attn_nm(data) |> select( any_of(c("mh_p_asr__synd__attn_nm", vars_mh_p_asr__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__attn_nm(data) |> select( any_of(c("mh_p_asr__synd__attn_nm", vars_mh_p_asr__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__ext_nm
Adult Self Report [Parent] (Syndrome Scale - Externalizing): Number
missing
Summarized variables:
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
mh_p_asr__rule_001
mh_p_asr__rule_002
mh_p_asr__rule_003
mh_p_asr__rule_004
mh_p_asr__rule__hypimp_001
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
mh_p_asr__aggr_001
mh_p_asr__aggr_002
mh_p_asr__aggr_003
mh_p_asr__aggr_004
mh_p_asr__aggr_005
mh_p_asr__aggr_006
mh_p_asr__aggr__hypimp_001
mh_p_asr__aggr__antsoc_001
mh_p_asr__aggr__antsoc_002
mh_p_asr__aggr__antsoc_003
mh_p_asr__aggr__antsoc_004
mh_p_asr__aggr__antsoc_005
mh_p_asr__aggr__antsoc_006
mh_p_asr__aggr__antsoc_007
mh_p_asr__aggr__antsoc_008
Excluded values:
777
999
vars_mh_p_asr__synd__ext compute_mh_p_asr__synd__ext_nm( data, name = "mh_p_asr__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__ext compute_mh_p_asr__synd__ext_nm( data, name = "mh_p_asr__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__ext is vector of all column names
used to compute summary score of mh_p_asr__synd__ext scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__ext_nm(data) |> select( any_of(c("mh_p_asr__synd__ext_nm", vars_mh_p_asr__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__ext_nm(data) |> select( any_of(c("mh_p_asr__synd__ext_nm", vars_mh_p_asr__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__int_nm
Adult Self Report [Parent] (Syndrome Scale - Internalizing): Number
missing
Summarized variables:
mh_p_asr__anxdep_001
mh_p_asr__anxdep_002
mh_p_asr__anxdep_003
mh_p_asr__anxdep_004
mh_p_asr__anxdep_005
mh_p_asr__anxdep_006
mh_p_asr__anxdep__anx_001
mh_p_asr__anxdep__anx_002
mh_p_asr__anxdep__anx_003
mh_p_asr__anxdep__anx_004
mh_p_asr__anxdep__avoid_001
mh_p_asr__anxdep__avoid_002
mh_p_asr__anxdep__dep_001
mh_p_asr__anxdep__dep_002
mh_p_asr__anxdep__dep_003
mh_p_asr__anxdep__dep_004
mh_p_asr__anxdep__dep_005
mh_p_asr__anxdep__dep_006
mh_p_asr__som_001
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
vars_mh_p_asr__synd__int compute_mh_p_asr__synd__int_nm( data, name = "mh_p_asr__synd__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__int compute_mh_p_asr__synd__int_nm( data, name = "mh_p_asr__synd__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__int is vector of all column names
used to compute summary score of mh_p_asr__synd__int scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__int_nm(data) |> select( any_of(c("mh_p_asr__synd__int_nm", vars_mh_p_asr__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__int_nm(data) |> select( any_of(c("mh_p_asr__synd__int_nm", vars_mh_p_asr__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__intru_nm
Adult Self Report [Parent] (Syndrome Scale - Intrusive): Number
missing
Summarized variables:
mh_p_asr__intru_001
mh_p_asr__intru_002
mh_p_asr__intru_003
mh_p_asr__intru_004
mh_p_asr__intru_005
mh_p_asr__intru_006
Excluded values:
777
999
vars_mh_p_asr__synd__intru compute_mh_p_asr__synd__intru_nm( data, name = "mh_p_asr__synd__intru_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__intru compute_mh_p_asr__synd__intru_nm( data, name = "mh_p_asr__synd__intru_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__intru is vector of all column names
used to compute summary score of mh_p_asr__synd__intru scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__intru_nm(data) |> select( any_of(c("mh_p_asr__synd__intru_nm", vars_mh_p_asr__synd__intru)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__intru_nm(data) |> select( any_of(c("mh_p_asr__synd__intru_nm", vars_mh_p_asr__synd__intru)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__othpr_nm
Adult Self Report [Parent] (Syndrome Scale - Other problems): Number
missing
Summarized variables:
mh_p_asr__othpr_001
mh_p_asr__othpr_002
mh_p_asr__othpr_003
mh_p_asr__othpr_004
mh_p_asr__othpr_005
mh_p_asr__othpr_006
mh_p_asr__othpr_007
mh_p_asr__othpr_008
mh_p_asr__othpr_009
mh_p_asr__othpr_010
mh_p_asr__othpr_011
mh_p_asr__othpr__hypimp_001
mh_p_asr__othpr__hypimp_002
mh_p_asr__othpr__hypimp_003
mh_p_asr__othpr__antsoc_001
mh_p_asr__othpr__antsoc_002
mh_p_asr__othpr__anx_001
mh_p_asr__othpr__anx_002
mh_p_asr__othpr__avoid_001
mh_p_asr__othpr__dep_001
mh_p_asr__othpr__dep_002
Excluded values:
777
999
vars_mh_p_asr__synd__othpr compute_mh_p_asr__synd__othpr_nm( data, name = "mh_p_asr__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__othpr compute_mh_p_asr__synd__othpr_nm( data, name = "mh_p_asr__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__othpr is vector of all column names
used to compute summary score of mh_p_asr__synd__othpr scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__othpr_nm(data) |> select( any_of(c("mh_p_asr__synd__othpr_nm", vars_mh_p_asr__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__othpr_nm(data) |> select( any_of(c("mh_p_asr__synd__othpr_nm", vars_mh_p_asr__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__rule_nm
Adult Self Report [Parent] (Syndrome Scale - Rule breaking behavior):
Number missing
Summarized variables:
mh_p_asr__rule_001
mh_p_asr__rule_002
mh_p_asr__rule_003
mh_p_asr__rule_004
mh_p_asr__rule__hypimp_001
mh_p_asr__rule__antsoc_001
mh_p_asr__rule__antsoc_002
mh_p_asr__rule__antsoc_003
mh_p_asr__rule__antsoc_004
mh_p_asr__rule__antsoc_005
mh_p_asr__rule__antsoc_006
mh_p_asr__rule__antsoc_007
mh_p_asr__rule__antsoc_008
mh_p_asr__rule__antsoc_009
Excluded values:
777
999
vars_mh_p_asr__synd__rule compute_mh_p_asr__synd__rule_nm( data, name = "mh_p_asr__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__rule compute_mh_p_asr__synd__rule_nm( data, name = "mh_p_asr__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__rule is vector of all column names
used to compute summary score of mh_p_asr__synd__rule scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__rule_nm(data) |> select( any_of(c("mh_p_asr__synd__rule_nm", vars_mh_p_asr__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__rule_nm(data) |> select( any_of(c("mh_p_asr__synd__rule_nm", vars_mh_p_asr__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__som_nm
Adult Self Report [Parent] (Syndrome Scale - Somatic complaints):
Number missing
Summarized variables:
mh_p_asr__som_001
mh_p_asr__som__dep_001
mh_p_asr__som__dep_002
mh_p_asr__som__somat_001
mh_p_asr__som__somat_002
mh_p_asr__som__somat_003
mh_p_asr__som__somat_004
mh_p_asr__som__somat_005
mh_p_asr__som__somat_006
mh_p_asr__som__somat_007
mh_p_asr__som__somat_008
mh_p_asr__som__somat_009
Excluded values:
777
999
vars_mh_p_asr__synd__som compute_mh_p_asr__synd__som_nm( data, name = "mh_p_asr__synd__som_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__som compute_mh_p_asr__synd__som_nm( data, name = "mh_p_asr__synd__som_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__som is vector of all column names
used to compute summary score of mh_p_asr__synd__som scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__som_nm(data) |> select( any_of(c("mh_p_asr__synd__som_nm", vars_mh_p_asr__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__som_nm(data) |> select( any_of(c("mh_p_asr__synd__som_nm", vars_mh_p_asr__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__tho_nm
Adult Self Report [Parent] (Syndrome Scale - Thought problems): Number
missing
Summarized variables:
mh_p_asr__tho_001
mh_p_asr__tho_002
mh_p_asr__tho_003
mh_p_asr__tho_004
mh_p_asr__tho_005
mh_p_asr__tho_006
mh_p_asr__tho_007
mh_p_asr__tho_008
mh_p_asr__tho__hypimp_001
mh_p_asr__tho__dep_001
Excluded values:
777
999
vars_mh_p_asr__synd__tho compute_mh_p_asr__synd__tho_nm( data, name = "mh_p_asr__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__tho compute_mh_p_asr__synd__tho_nm( data, name = "mh_p_asr__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__tho is vector of all column names
used to compute summary score of mh_p_asr__synd__tho scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__tho_nm(data) |> select( any_of(c("mh_p_asr__synd__tho_nm", vars_mh_p_asr__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__tho_nm(data) |> select( any_of(c("mh_p_asr__synd__tho_nm", vars_mh_p_asr__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_asr__synd__wthdr_nm
Adult Self Report [Parent] (Syndrome Scale - Withdrawn): Number
missing
Summarized variables:
mh_p_asr__wthdr_001
mh_p_asr__wthdr_002
mh_p_asr__wthdr_003
mh_p_asr__wthdr_004
mh_p_asr__wthdr__avoid_001
mh_p_asr__wthdr__avoid_002
mh_p_asr__wthdr__avoid_003
mh_p_asr__wthdr__avoid_004
mh_p_asr__wthdr__dep_001
Excluded values:
777
999
vars_mh_p_asr__synd__wthdr compute_mh_p_asr__synd__wthdr_nm( data, name = "mh_p_asr__synd__wthdr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_asr__synd__wthdr compute_mh_p_asr__synd__wthdr_nm( data, name = "mh_p_asr__synd__wthdr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_asr__synd__wthdr is vector of all column names
used to compute summary score of mh_p_asr__synd__wthdr scores.
tbl. see combine.
## Not run: compute_mh_p_asr__synd__wthdr_nm(data) |> select( any_of(c("mh_p_asr__synd__wthdr_nm", vars_mh_p_asr__synd__wthdr)) ) ## End(Not run)## Not run: compute_mh_p_asr__synd__wthdr_nm(data) |> select( any_of(c("mh_p_asr__synd__wthdr_nm", vars_mh_p_asr__synd__wthdr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl_nm
Child Behavior Checklist [Parent] (Syndrome Scale): Number missing
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep_001
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
mh_p_cbcl__wthdep_005
mh_p_cbcl__soc_004
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__anxdep_002
mh_p_cbcl__attn_001
mh_p_cbcl__attn_004
mh_p_cbcl__rule_001
mh_p_cbcl__rule_006
mh_p_cbcl__rule_002
mh_p_cbcl__rule_003
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_004
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__othpr_001
mh_p_cbcl__othpr_002
mh_p_cbcl__othpr_009
mh_p_cbcl__othpr_010
mh_p_cbcl__othpr_011
mh_p_cbcl__othpr_012
mh_p_cbcl__othpr_003
mh_p_cbcl__othpr_004
mh_p_cbcl__othpr_005
mh_p_cbcl__othpr_006
mh_p_cbcl__othpr_007
mh_p_cbcl__othpr_008
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_008
mh_p_cbcl__tho_009
mh_p_cbcl__tho_012
Excluded values:
777
999
vars_mh_p_cbcl compute_mh_p_cbcl_nm( data, name = "mh_p_cbcl_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl compute_mh_p_cbcl_nm( data, name = "mh_p_cbcl_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl is vector of all column names
used to compute summary score of mh_p_cbcl scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl_nm(data) |> select( any_of(c("mh_p_cbcl_nm", vars_mh_p_cbcl)) ) ## End(Not run)## Not run: compute_mh_p_cbcl_nm(data) |> select( any_of(c("mh_p_cbcl_nm", vars_mh_p_cbcl)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__adhd_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - ADHD):
Number missing
Summarized variables:
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__othpr__adhd_001
Excluded values:
777
999
vars_mh_p_cbcl__dsm__adhd compute_mh_p_cbcl__dsm__adhd_nm( data, name = "mh_p_cbcl__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__adhd compute_mh_p_cbcl__dsm__adhd_nm( data, name = "mh_p_cbcl__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__adhd is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__adhd scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__adhd_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_nm", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__adhd_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__adhd_nm", vars_mh_p_cbcl__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__anx_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Anxiety):
Number missing
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__anx_006
Excluded values:
777
999
vars_mh_p_cbcl__dsm__anx compute_mh_p_cbcl__dsm__anx_nm( data, name = "mh_p_cbcl__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__anx compute_mh_p_cbcl__dsm__anx_nm( data, name = "mh_p_cbcl__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__anx is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__anx scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__anx_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_nm", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__anx_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__anx_nm", vars_mh_p_cbcl__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__cond_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Conduct
problems): Number missing
Summarized variables:
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule__cond_011
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
vars_mh_p_cbcl__dsm__cond compute_mh_p_cbcl__dsm__cond_nm( data, name = "mh_p_cbcl__dsm__cond_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__cond compute_mh_p_cbcl__dsm__cond_nm( data, name = "mh_p_cbcl__dsm__cond_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__cond is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__cond scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__cond_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_nm", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__cond_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__cond_nm", vars_mh_p_cbcl__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__dep_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Depressive
problems): Number missing
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__tho__dep_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__som__dep_001
mh_p_cbcl__tho__dep_002
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
vars_mh_p_cbcl__dsm__dep compute_mh_p_cbcl__dsm__dep_nm( data, name = "mh_p_cbcl__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__dep compute_mh_p_cbcl__dsm__dep_nm( data, name = "mh_p_cbcl__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__dep is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__dep scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__dep_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_nm", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__dep_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__dep_nm", vars_mh_p_cbcl__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__opp_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Oppositional
Defiant problems): Number missing
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr__opp_005
Excluded values:
777
999
vars_mh_p_cbcl__dsm__opp compute_mh_p_cbcl__dsm__opp_nm( data, name = "mh_p_cbcl__dsm__opp_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__opp compute_mh_p_cbcl__dsm__opp_nm( data, name = "mh_p_cbcl__dsm__opp_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__opp is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__opp scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__opp_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_nm", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__opp_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__opp_nm", vars_mh_p_cbcl__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__dsm__somat_nm
Child Behavior Checklist [Parent] (DSM-5 Oriented Scale - Somatic
complaints): Number missing
Summarized variables:
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
vars_mh_p_cbcl__dsm__somat compute_mh_p_cbcl__dsm__somat_nm( data, name = "mh_p_cbcl__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__dsm__somat compute_mh_p_cbcl__dsm__somat_nm( data, name = "mh_p_cbcl__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__dsm__somat is vector of all column names
used to compute summary score of mh_p_cbcl__dsm__somat scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__dsm__somat_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_nm", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__dsm__somat_nm(data) |> select( any_of(c("mh_p_cbcl__dsm__somat_nm", vars_mh_p_cbcl__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__ocd_nm
Child Behavior Checklist [Parent] (Obsessive-Compulsive Problems):
Number missing
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__tho_007
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
Excluded values:
777
999
vars_mh_p_cbcl__ocd compute_mh_p_cbcl__ocd_nm( data, name = "mh_p_cbcl__ocd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__ocd compute_mh_p_cbcl__ocd_nm( data, name = "mh_p_cbcl__ocd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__ocd is vector of all column names
used to compute summary score of mh_p_cbcl__ocd scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__ocd_nm(data) |> select( any_of(c("mh_p_cbcl__ocd_nm", vars_mh_p_cbcl__ocd)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__ocd_nm(data) |> select( any_of(c("mh_p_cbcl__ocd_nm", vars_mh_p_cbcl__ocd)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__sct_nm
Child Behavior Checklist [Parent] (Sluggish Cognitive Tempo): Number
missing
Summarized variables:
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn_005
Excluded values:
777
999
vars_mh_p_cbcl__sct compute_mh_p_cbcl__sct_nm( data, name = "mh_p_cbcl__sct_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__sct compute_mh_p_cbcl__sct_nm( data, name = "mh_p_cbcl__sct_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__sct is vector of all column names
used to compute summary score of mh_p_cbcl__sct scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__sct_nm(data) |> select( any_of(c("mh_p_cbcl__sct_nm", vars_mh_p_cbcl__sct)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__sct_nm(data) |> select( any_of(c("mh_p_cbcl__sct_nm", vars_mh_p_cbcl__sct)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__strs_nm
Child Behavior Checklist [Parent] (Stress): Number missing
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__tho_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__soc__anx_001
mh_p_cbcl__wthdep_005
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__soc_004
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__wthdep_003
mh_p_cbcl__aggr_004
Excluded values:
777
999
vars_mh_p_cbcl__strs compute_mh_p_cbcl__strs_nm( data, name = "mh_p_cbcl__strs_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__strs compute_mh_p_cbcl__strs_nm( data, name = "mh_p_cbcl__strs_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__strs is vector of all column names
used to compute summary score of mh_p_cbcl__strs scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__strs_nm(data) |> select( any_of(c("mh_p_cbcl__strs_nm", vars_mh_p_cbcl__strs)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__strs_nm(data) |> select( any_of(c("mh_p_cbcl__strs_nm", vars_mh_p_cbcl__strs)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__aggr_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Aggressive
behavior): Number missing
Summarized variables:
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
vars_mh_p_cbcl__synd__aggr compute_mh_p_cbcl__synd__aggr_nm( data, name = "mh_p_cbcl__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__aggr compute_mh_p_cbcl__synd__aggr_nm( data, name = "mh_p_cbcl__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__aggr is vector of all column names
used to compute summary score of mh_p_cbcl__synd__aggr scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__aggr_nm(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_nm", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__aggr_nm(data) |> select( any_of(c("mh_p_cbcl__synd__aggr_nm", vars_mh_p_cbcl__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__anxdep_nm
Child Behavior Checklist [Parent] (Syndrome Scale -
Anxious/Depressed): Number missing
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
Excluded values:
777
999
vars_mh_p_cbcl__synd__anxdep compute_mh_p_cbcl__synd__anxdep_nm( data, name = "mh_p_cbcl__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__anxdep compute_mh_p_cbcl__synd__anxdep_nm( data, name = "mh_p_cbcl__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__anxdep is vector of all column names
used to compute summary score of mh_p_cbcl__synd__anxdep scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__anxdep_nm(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_nm", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__anxdep_nm(data) |> select( any_of(c("mh_p_cbcl__synd__anxdep_nm", vars_mh_p_cbcl__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__attn_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Attention
problems): Number missing
Summarized variables:
mh_p_cbcl__attn_001
mh_p_cbcl__attn__adhd_001
mh_p_cbcl__attn__adhd_002
mh_p_cbcl__attn__adhd_003
mh_p_cbcl__attn_002
mh_p_cbcl__attn_003
mh_p_cbcl__attn__adhd_004
mh_p_cbcl__attn_004
mh_p_cbcl__attn__adhd_005
mh_p_cbcl__attn_005
Excluded values:
777
999
vars_mh_p_cbcl__synd__attn compute_mh_p_cbcl__synd__attn_nm( data, name = "mh_p_cbcl__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__attn compute_mh_p_cbcl__synd__attn_nm( data, name = "mh_p_cbcl__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__attn is vector of all column names
used to compute summary score of mh_p_cbcl__synd__attn scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__attn_nm(data) |> select( any_of(c("mh_p_cbcl__synd__attn_nm", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__attn_nm(data) |> select( any_of(c("mh_p_cbcl__synd__attn_nm", vars_mh_p_cbcl__synd__attn)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__ext_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Externalizing):
Number missing
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
mh_p_cbcl__aggr__opp_001
mh_p_cbcl__aggr__adhd_001
mh_p_cbcl__aggr__cond_001
mh_p_cbcl__aggr_001
mh_p_cbcl__aggr_002
mh_p_cbcl__aggr__cond_002
mh_p_cbcl__aggr__opp_002
mh_p_cbcl__aggr__opp_003
mh_p_cbcl__aggr__cond_003
mh_p_cbcl__aggr__cond_004
mh_p_cbcl__aggr_003
mh_p_cbcl__aggr__opp_004
mh_p_cbcl__aggr_004
mh_p_cbcl__aggr_005
mh_p_cbcl__aggr_006
mh_p_cbcl__aggr_007
mh_p_cbcl__aggr__opp_005
mh_p_cbcl__aggr__cond_005
Excluded values:
777
999
vars_mh_p_cbcl__synd__ext compute_mh_p_cbcl__synd__ext_nm( data, name = "mh_p_cbcl__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__ext compute_mh_p_cbcl__synd__ext_nm( data, name = "mh_p_cbcl__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__ext is vector of all column names
used to compute summary score of mh_p_cbcl__synd__ext scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__ext_nm(data) |> select( any_of(c("mh_p_cbcl__synd__ext_nm", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__ext_nm(data) |> select( any_of(c("mh_p_cbcl__synd__ext_nm", vars_mh_p_cbcl__synd__ext)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__int_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Internalizing):
Number missing
Summarized variables:
mh_p_cbcl__anxdep__anx_007
mh_p_cbcl__anxdep__dep_001
mh_p_cbcl__anxdep__anx_001
mh_p_cbcl__anxdep__anx_002
mh_p_cbcl__anxdep__anx_003
mh_p_cbcl__anxdep_001
mh_p_cbcl__anxdep_002
mh_p_cbcl__anxdep__dep_002
mh_p_cbcl__anxdep__anx_004
mh_p_cbcl__anxdep__anx_005
mh_p_cbcl__anxdep__dep_003
mh_p_cbcl__anxdep__anx_006
mh_p_cbcl__anxdep__dep_004
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
vars_mh_p_cbcl__synd__int compute_mh_p_cbcl__synd__int_nm( data, name = "mh_p_cbcl__synd__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__int compute_mh_p_cbcl__synd__int_nm( data, name = "mh_p_cbcl__synd__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__int is vector of all column names
used to compute summary score of mh_p_cbcl__synd__int scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__int_nm(data) |> select( any_of(c("mh_p_cbcl__synd__int_nm", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__int_nm(data) |> select( any_of(c("mh_p_cbcl__synd__int_nm", vars_mh_p_cbcl__synd__int)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__othpr_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Other problems):
Number missing
Summarized variables:
mh_p_cbcl__othpr_001
mh_p_cbcl__othpr_002
mh_p_cbcl__othpr_009
mh_p_cbcl__othpr_010
mh_p_cbcl__othpr_011
mh_p_cbcl__othpr_012
mh_p_cbcl__othpr__cond_001
mh_p_cbcl__othpr__dep_001
mh_p_cbcl__othpr_003
mh_p_cbcl__othpr_004
mh_p_cbcl__othpr_005
mh_p_cbcl__othpr_006
mh_p_cbcl__othpr_007
mh_p_cbcl__othpr__dep_002
mh_p_cbcl__othpr__adhd_001
mh_p_cbcl__othpr_008
Excluded values:
777
999
vars_mh_p_cbcl__synd__othpr compute_mh_p_cbcl__synd__othpr_nm( data, name = "mh_p_cbcl__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__othpr compute_mh_p_cbcl__synd__othpr_nm( data, name = "mh_p_cbcl__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__othpr is vector of all column names
used to compute summary score of mh_p_cbcl__synd__othpr scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__othpr_nm(data) |> select( any_of(c("mh_p_cbcl__synd__othpr_nm", vars_mh_p_cbcl__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__othpr_nm(data) |> select( any_of(c("mh_p_cbcl__synd__othpr_nm", vars_mh_p_cbcl__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__rule_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Rule breaking
behavior): Number missing
Summarized variables:
mh_p_cbcl__rule_001
mh_p_cbcl__rule__cond_010
mh_p_cbcl__rule_006
mh_p_cbcl__rule__cond_011
mh_p_cbcl__rule__cond_001
mh_p_cbcl__rule__cond_002
mh_p_cbcl__rule__cond_003
mh_p_cbcl__rule__cond_004
mh_p_cbcl__rule_002
mh_p_cbcl__rule__cond_005
mh_p_cbcl__rule__cond_006
mh_p_cbcl__rule_003
mh_p_cbcl__rule__cond_007
mh_p_cbcl__rule__cond_008
mh_p_cbcl__rule__cond_009
mh_p_cbcl__rule_004
mh_p_cbcl__rule_005
Excluded values:
777
999
vars_mh_p_cbcl__synd__rule compute_mh_p_cbcl__synd__rule_nm( data, name = "mh_p_cbcl__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__rule compute_mh_p_cbcl__synd__rule_nm( data, name = "mh_p_cbcl__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__rule is vector of all column names
used to compute summary score of mh_p_cbcl__synd__rule scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__rule_nm(data) |> select( any_of(c("mh_p_cbcl__synd__rule_nm", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__rule_nm(data) |> select( any_of(c("mh_p_cbcl__synd__rule_nm", vars_mh_p_cbcl__synd__rule)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__soc_nm
Child Behavior Checklist [Parent] (Syndrome Scale -Social): Number
missing
Summarized variables:
mh_p_cbcl__soc__anx_001
mh_p_cbcl__soc_001
mh_p_cbcl__soc_002
mh_p_cbcl__soc_003
mh_p_cbcl__soc_004
mh_p_cbcl__soc_005
mh_p_cbcl__soc_006
mh_p_cbcl__soc_007
mh_p_cbcl__soc_008
mh_p_cbcl__soc_009
mh_p_cbcl__soc_010
Excluded values:
777
999
vars_mh_p_cbcl__synd__soc compute_mh_p_cbcl__synd__soc_nm( data, name = "mh_p_cbcl__synd__soc_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__soc compute_mh_p_cbcl__synd__soc_nm( data, name = "mh_p_cbcl__synd__soc_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__soc is vector of all column names
used to compute summary score of mh_p_cbcl__synd__soc scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__soc_nm(data) |> select( any_of(c("mh_p_cbcl__synd__soc_nm", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__soc_nm(data) |> select( any_of(c("mh_p_cbcl__synd__soc_nm", vars_mh_p_cbcl__synd__soc)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__som_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Somatic
complaints): Number missing
Summarized variables:
mh_p_cbcl__som__anx_001
mh_p_cbcl__som_001
mh_p_cbcl__som_002
mh_p_cbcl__som__dep_001
mh_p_cbcl__som__somat_001
mh_p_cbcl__som__somat_002
mh_p_cbcl__som__somat_003
mh_p_cbcl__som__somat_004
mh_p_cbcl__som__somat_005
mh_p_cbcl__som__somat_006
mh_p_cbcl__som__somat_007
Excluded values:
777
999
vars_mh_p_cbcl__synd__som compute_mh_p_cbcl__synd__som_nm( data, name = "mh_p_cbcl__synd__som_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__som compute_mh_p_cbcl__synd__som_nm( data, name = "mh_p_cbcl__synd__som_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__som is vector of all column names
used to compute summary score of mh_p_cbcl__synd__som scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__som_nm(data) |> select( any_of(c("mh_p_cbcl__synd__som_nm", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__som_nm(data) |> select( any_of(c("mh_p_cbcl__synd__som_nm", vars_mh_p_cbcl__synd__som)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__tho_nm
Child Behavior Checklist [Parent] (Syndrome Scale - Thought problems):
Number missing
Summarized variables:
mh_p_cbcl__tho_001
mh_p_cbcl__tho__dep_003
mh_p_cbcl__tho__dep_001
mh_p_cbcl__tho_002
mh_p_cbcl__tho_003
mh_p_cbcl__tho_004
mh_p_cbcl__tho_005
mh_p_cbcl__tho_006
mh_p_cbcl__tho_007
mh_p_cbcl__tho_008
mh_p_cbcl__tho__dep_002
mh_p_cbcl__tho_009
mh_p_cbcl__tho_010
mh_p_cbcl__tho_011
mh_p_cbcl__tho_012
Excluded values:
777
999
vars_mh_p_cbcl__synd__tho compute_mh_p_cbcl__synd__tho_nm( data, name = "mh_p_cbcl__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__tho compute_mh_p_cbcl__synd__tho_nm( data, name = "mh_p_cbcl__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__tho is vector of all column names
used to compute summary score of mh_p_cbcl__synd__tho scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__tho_nm(data) |> select( any_of(c("mh_p_cbcl__synd__tho_nm", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__tho_nm(data) |> select( any_of(c("mh_p_cbcl__synd__tho_nm", vars_mh_p_cbcl__synd__tho)) ) ## End(Not run)
Computes the summary score mh_p_cbcl__synd__wthdep_nm
Child Behavior Checklist [Parent] (Syndrome Scale -
Withdrawn/Depressed): Number missing
Summarized variables:
mh_p_cbcl__wthdep__dep_001
mh_p_cbcl__wthdep__dep_002
mh_p_cbcl__wthdep__dep_003
mh_p_cbcl__wthdep_005
mh_p_cbcl__wthdep_001
mh_p_cbcl__wthdep_002
mh_p_cbcl__wthdep_003
mh_p_cbcl__wthdep_004
Excluded values:
777
999
vars_mh_p_cbcl__synd__wthdep compute_mh_p_cbcl__synd__wthdep_nm( data, name = "mh_p_cbcl__synd__wthdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_p_cbcl__synd__wthdep compute_mh_p_cbcl__synd__wthdep_nm( data, name = "mh_p_cbcl__synd__wthdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_p_cbcl__synd__wthdep is vector of all column names
used to compute summary score of mh_p_cbcl__synd__wthdep scores.
tbl. see combine.
## Not run: compute_mh_p_cbcl__synd__wthdep_nm(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_nm", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_p_cbcl__synd__wthdep_nm(data) |> select( any_of(c("mh_p_cbcl__synd__wthdep_nm", vars_mh_p_cbcl__synd__wthdep)) ) ## End(Not run)
Computes the summary score mh_p_ders__attun_mean
Difficulties in Emotion Regulation Scale [Parent] (Attuned): Mean
Summarized variables:
mh_p_ders__attun_001
mh_p_ders__attun_002
mh_p_ders__attun_003
mh_p_ders__attun_004
mh_p_ders__attun_005
mh_p_ders__attun_006
Excluded values:
999
777
Validation criterion: maximally 1 of 6 items missing
vars_mh_p_ders__attun compute_mh_p_ders__attun_mean( data, name = "mh_p_ders__attun_mean", max_na = 1, exclude = c("999", "777"), combine = TRUE )vars_mh_p_ders__attun compute_mh_p_ders__attun_mean( data, name = "mh_p_ders__attun_mean", max_na = 1, exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ders__attun is vector of all column names
used to compute summary score of mh_p_ders__attun scores.
tbl. see combine.
## Not run: compute_mh_p_ders__attun_mean(data) |> select( any_of(c("mh_p_ders__attun_mean", vars_mh_p_ders__attun)) ) ## End(Not run)## Not run: compute_mh_p_ders__attun_mean(data) |> select( any_of(c("mh_p_ders__attun_mean", vars_mh_p_ders__attun)) ) ## End(Not run)
Computes the summary score mh_p_ders__catast_mean
Difficulties in Emotion Regulation Scale [Parent] (Catastrophize):
Mean
Summarized variables:
mh_p_ders__catast_001
mh_p_ders__catast_002
mh_p_ders__catast_003
mh_p_ders__catast_004
mh_p_ders__catast_005
mh_p_ders__catast_006
mh_p_ders__catast_007
mh_p_ders__catast_008
mh_p_ders__catast_009
mh_p_ders__catast_010
mh_p_ders__catast_011
mh_p_ders__catast_012
Excluded values:
999
777
Validation criterion: maximally 2 of 12 items missing
vars_mh_p_ders__catast compute_mh_p_ders__catast_mean( data, name = "mh_p_ders__catast_mean", max_na = 2, exclude = c("999", "777"), combine = TRUE )vars_mh_p_ders__catast compute_mh_p_ders__catast_mean( data, name = "mh_p_ders__catast_mean", max_na = 2, exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ders__catast is vector of all column names
used to compute summary score of mh_p_ders__catast scores.
tbl. see combine.
## Not run: compute_mh_p_ders__catast_mean(data) |> select( any_of(c("mh_p_ders__catast_mean", vars_mh_p_ders__catast)) ) ## End(Not run)## Not run: compute_mh_p_ders__catast_mean(data) |> select( any_of(c("mh_p_ders__catast_mean", vars_mh_p_ders__catast)) ) ## End(Not run)
Computes the summary score mh_p_ders__distract_mean
Difficulties in Emotion Regulation Scale [Parent] (Distracted): Mean
Summarized variables:
mh_p_ders__distract_001
mh_p_ders__distract_002
mh_p_ders__distract_003
mh_p_ders__distract_004
Excluded values:
999
777
Validation criterion: none of 4 items missing
vars_mh_p_ders__distract compute_mh_p_ders__distract_mean( data, name = "mh_p_ders__distract_mean", max_na = 0, exclude = c("999", "777"), combine = TRUE )vars_mh_p_ders__distract compute_mh_p_ders__distract_mean( data, name = "mh_p_ders__distract_mean", max_na = 0, exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ders__distract is vector of all column names
used to compute summary score of mh_p_ders__distract scores.
tbl. see combine.
## Not run: compute_mh_p_ders__distract_mean(data) |> select( any_of(c("mh_p_ders__distract_mean", vars_mh_p_ders__distract)) ) ## End(Not run)## Not run: compute_mh_p_ders__distract_mean(data) |> select( any_of(c("mh_p_ders__distract_mean", vars_mh_p_ders__distract)) ) ## End(Not run)
Computes the summary score mh_p_ders__negscnd_mean
Difficulties in Emotion Regulation Scale [Parent] (Negative
Secondary): Mean
Summarized variables:
mh_p_ders__negscnd_001
mh_p_ders__negscnd_002
mh_p_ders__negscnd_003
mh_p_ders__negscnd_004
mh_p_ders__negscnd_005
mh_p_ders__negscnd_006
mh_p_ders__negscnd_007
Excluded values:
999
777
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_ders__negscnd compute_mh_p_ders__negscnd_mean( data, name = "mh_p_ders__negscnd_mean", max_na = 1, exclude = c("999", "777"), combine = TRUE )vars_mh_p_ders__negscnd compute_mh_p_ders__negscnd_mean( data, name = "mh_p_ders__negscnd_mean", max_na = 1, exclude = c("999", "777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ders__negscnd is vector of all column names
used to compute summary score of mh_p_ders__negscnd scores.
tbl. see combine.
## Not run: compute_mh_p_ders__negscnd_mean(data) |> select( any_of(c("mh_p_ders__negscnd_mean", vars_mh_p_ders__negscnd)) ) ## End(Not run)## Not run: compute_mh_p_ders__negscnd_mean(data) |> select( any_of(c("mh_p_ders__negscnd_mean", vars_mh_p_ders__negscnd)) ) ## End(Not run)
Computes the summary score mh_p_eatq__actv_mean
Early Adolescent Temperament Questionnaire [Parent] (Activation): Mean
Summarized variables:
mh_p_eatq__actv_001
mh_p_eatq__actv_002
mh_p_eatq__actv_003
mh_p_eatq__actv_004
mh_p_eatq__actv_005
mh_p_eatq__actv_006
mh_p_eatq__actv_007
Excluded values: none
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_eatq__actv compute_mh_p_eatq__actv_mean( data, name = "mh_p_eatq__actv_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__actv compute_mh_p_eatq__actv_mean( data, name = "mh_p_eatq__actv_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__actv is a character vector of all column names
used to compute summary score of mh_p_eatq__actv_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__actv_mean(data) select( data, any_of(c("mh_p_eatq__actv_mean", vars_mh_p_eatq__actv)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__actv_mean(data) select( data, any_of(c("mh_p_eatq__actv_mean", vars_mh_p_eatq__actv)) ) ## End(Not run)
Computes the summary score mh_p_eatq__affl_mean
Early Adolescent Temperament Questionnaire [Parent] (Affiliation):
Mean
Summarized variables:
mh_p_eatq__affl_001
mh_p_eatq__affl_002
mh_p_eatq__affl_003
mh_p_eatq__affl_004
mh_p_eatq__affl_005
mh_p_eatq__affl_006
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_mh_p_eatq__affl compute_mh_p_eatq__affl_mean( data, name = "mh_p_eatq__affl_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__affl compute_mh_p_eatq__affl_mean( data, name = "mh_p_eatq__affl_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__affl is a character vector of all column names
used to compute summary score of mh_p_eatq__affl_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__affl_mean(data) select( data, any_of(c("mh_p_eatq__affl_mean", vars_mh_p_eatq__affl)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__affl_mean(data) select( data, any_of(c("mh_p_eatq__affl_mean", vars_mh_p_eatq__affl)) ) ## End(Not run)
Computes the summary score mh_p_eatq__aggr_mean
Early Adolescent Temperament Questionnaire [Parent] (Aggression): Mean
Summarized variables:
mh_p_eatq__aggr_001
mh_p_eatq__aggr_002
mh_p_eatq__aggr_003
mh_p_eatq__aggr_004
mh_p_eatq__aggr_005
mh_p_eatq__aggr_006
mh_p_eatq__aggr_007
Excluded values: none
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_eatq__aggr compute_mh_p_eatq__aggr_mean( data, name = "mh_p_eatq__aggr_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__aggr compute_mh_p_eatq__aggr_mean( data, name = "mh_p_eatq__aggr_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__aggr is a character vector of all column names
used to compute summary score of mh_p_eatq__aggr_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__aggr_mean(data) select( data, any_of(c("mh_p_eatq__aggr_mean", vars_mh_p_eatq__aggr)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__aggr_mean(data) select( data, any_of(c("mh_p_eatq__aggr_mean", vars_mh_p_eatq__aggr)) ) ## End(Not run)
Computes the summary score mh_p_eatq__attn_mean
Early Adolescent Temperament Questionnaire [Parent] (Attention): Mean
Summarized variables:
mh_p_eatq__attn_001
mh_p_eatq__attn_002
mh_p_eatq__attn_003
mh_p_eatq__attn_004
mh_p_eatq__attn_005
mh_p_eatq__attn_006
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_mh_p_eatq__attn compute_mh_p_eatq__attn_mean( data, name = "mh_p_eatq__attn_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__attn compute_mh_p_eatq__attn_mean( data, name = "mh_p_eatq__attn_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__attn is a character vector of all column names
used to compute summary score of mh_p_eatq__attn_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__attn_mean(data) select( data, any_of(c("mh_p_eatq__attn_mean", vars_mh_p_eatq__attn)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__attn_mean(data) select( data, any_of(c("mh_p_eatq__attn_mean", vars_mh_p_eatq__attn)) ) ## End(Not run)
Computes the summary score mh_p_eatq__depm_mean
Early Adolescent Temperament Questionnaire [Parent] (Depressive Mood):
Mean
Summarized variables:
mh_p_eatq__depm_001
mh_p_eatq__depm_002
mh_p_eatq__depm_003
mh_p_eatq__depm_004
mh_p_eatq__depm_005
Excluded values: none
Validation criterion: maximally 1 of 5 items missing
vars_mh_p_eatq__depm compute_mh_p_eatq__depm_mean( data, name = "mh_p_eatq__depm_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__depm compute_mh_p_eatq__depm_mean( data, name = "mh_p_eatq__depm_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__depm is a character vector of all column names
used to compute summary score of mh_p_eatq__depm_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__depm_mean(data) select( data, any_of(c("mh_p_eatq__depm_mean", vars_mh_p_eatq__depm)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__depm_mean(data) select( data, any_of(c("mh_p_eatq__depm_mean", vars_mh_p_eatq__depm)) ) ## End(Not run)
Computes the summary score mh_p_eatq__fear_mean
Early Adolescent Temperament Questionnaire [Parent] (Fear): Mean
Summarized variables:
mh_p_eatq__fear_001
mh_p_eatq__fear_002
mh_p_eatq__fear_003
mh_p_eatq__fear_004
mh_p_eatq__fear_005
mh_p_eatq__fear_006
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_mh_p_eatq__fear compute_mh_p_eatq__fear_mean( data, name = "mh_p_eatq__fear_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__fear compute_mh_p_eatq__fear_mean( data, name = "mh_p_eatq__fear_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__fear is a character vector of all column names
used to compute summary score of mh_p_eatq__fear_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__fear_mean(data) select( data, any_of(c( "mh_p_eatq__fear_mean", vars_mh_p_eatq__fear )) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__fear_mean(data) select( data, any_of(c( "mh_p_eatq__fear_mean", vars_mh_p_eatq__fear )) ) ## End(Not run)
Computes the summary score mh_p_eatq__frust_mean
Early Adolescent Temperament Questionnaire [Parent] (Frustration):
Mean
Summarized variables:
mh_p_eatq__frust_001
mh_p_eatq__frust_002
mh_p_eatq__frust_003
mh_p_eatq__frust_004
mh_p_eatq__frust_005
mh_p_eatq__frust_006
Excluded values: none
Validation criterion: maximally 1 of 6 items missing
vars_mh_p_eatq__frust compute_mh_p_eatq__frust_mean( data, name = "mh_p_eatq__frust_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__frust compute_mh_p_eatq__frust_mean( data, name = "mh_p_eatq__frust_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__frust is a character vector of all column names
used to compute summary score of mh_p_eatq__frust_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__frust_mean(data) select( data, any_of(c("mh_p_eatq__frust_mean", vars_mh_p_eatq__frust)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__frust_mean(data) select( data, any_of(c("mh_p_eatq__frust_mean", vars_mh_p_eatq__frust)) ) ## End(Not run)
Computes the summary score mh_p_eatq__inhib_mean
Early Adolescent Temperament Questionnaire [Parent] (Inhibition): Mean
Summarized variables:
mh_p_eatq__inhib_001
mh_p_eatq__inhib_002
mh_p_eatq__inhib_003
mh_p_eatq__inhib_004
mh_p_eatq__inhib_005
Excluded values: none
Validation criterion: maximally 1 of 5 items missing
vars_mh_p_eatq__inhib compute_mh_p_eatq__inhib_mean( data, name = "mh_p_eatq__inhib_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__inhib compute_mh_p_eatq__inhib_mean( data, name = "mh_p_eatq__inhib_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__inhib is a character vector of all column names
used to compute summary score of mh_p_eatq__inhib_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__inhib_mean(data) select( data, any_of(c("mh_p_eatq__inhib_mean", vars_mh_p_eatq__inhib)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__inhib_mean(data) select( data, any_of(c("mh_p_eatq__inhib_mean", vars_mh_p_eatq__inhib)) ) ## End(Not run)
Computes the summary score mh_p_eatq__shy_mean
Early Adolescent Temperament Questionnaire [Parent] (Shyness): Mean
Summarized variables:
mh_p_eatq__shy_001
mh_p_eatq__shy_002
mh_p_eatq__shy_003
mh_p_eatq__shy_004
mh_p_eatq__shy_005
Excluded values: none
Validation criterion: maximally 1 of 5 items missing
vars_mh_p_eatq__shy compute_mh_p_eatq__shy_mean( data, name = "mh_p_eatq__shy_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__shy compute_mh_p_eatq__shy_mean( data, name = "mh_p_eatq__shy_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__shy is a character vector of all column names
used to compute summary score of mh_p_eatq__shy_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__shy_mean(data) select( data, any_of(c( "mh_p_eatq__shy_mean", vars_mh_p_eatq__shy )) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__shy_mean(data) select( data, any_of(c( "mh_p_eatq__shy_mean", vars_mh_p_eatq__shy )) ) ## End(Not run)
Computes the summary score mh_p_eatq__surg_mean
Early Adolescent Temperament Questionnaire [Parent] (Surgency): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_p_eatq__surg_001
mh_p_eatq__surg_002
mh_p_eatq__surg_003
mh_p_eatq__surg_004
mh_p_eatq__surg_005
mh_p_eatq__surg_006
mh_p_eatq__surg_007
mh_p_eatq__surg_008
mh_p_eatq__surg_009
Excluded values: none
Validation criterion: maximally 1 of 9 items missing
vars_mh_p_eatq__surg compute_mh_p_eatq__surg_mean( data, name = "mh_p_eatq__surg_mean", max_na = 1, combine = TRUE, revert = FALSE )vars_mh_p_eatq__surg compute_mh_p_eatq__surg_mean( data, name = "mh_p_eatq__surg_mean", max_na = 1, combine = TRUE, revert = FALSE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
revert |
logical, If |
vars_mh_p_eatq__surg is a character vector of all column names
used to compute summary score of mh_p_eatq__surg_mean.
tbl. The input data frame with the summary score appended as a new column.
## Not run: data <- compute_mh_p_eatq__surg_mean(data) select( data, any_of(c("mh_p_eatq__surg_mean", vars_mh_p_eatq__surg)) ) ## End(Not run)## Not run: data <- compute_mh_p_eatq__surg_mean(data) select( data, any_of(c("mh_p_eatq__surg_mean", vars_mh_p_eatq__surg)) ) ## End(Not run)
Computes the summary score mh_p_famhx__alc__moth__fath_indicator
(Family History [Parent] (Alcohol) Endorsed: Either parent)
Notes:
Following values are recoded as NA prior to any computation
777
888
999
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__alc__moth__fath_indicator compute_mh_p_famhx__alc__moth__fath_indicator( data, name = "mh_p_famhx__alc__moth__fath_indicator", combine = TRUE )vars_mh_p_famhx__alc__moth__fath_indicator compute_mh_p_famhx__alc__moth__fath_indicator( data, name = "mh_p_famhx__alc__moth__fath_indicator", combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__alc__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__alc__moth__fath_score
(Family History [Parent] (Alcohol) Endorsed: Parents overall)
Notes:
Following values are recoded as NA prior to any computation
777
888
999
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__alc__moth__fath_score compute_mh_p_famhx__alc__moth__fath_score( data, name = "mh_p_famhx__alc__moth__fath_score", combine = TRUE )vars_mh_p_famhx__alc__moth__fath_score compute_mh_p_famhx__alc__moth__fath_score( data, name = "mh_p_famhx__alc__moth__fath_score", combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__alc__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__dep__moth__fath_indicator
(Family History [Parent] (Depression) Endorsed: Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__dep__moth__fath_indicator compute_mh_p_famhx__dep__moth__fath_indicator( data, name = "mh_p_famhx__dep__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__dep__moth__fath_indicator compute_mh_p_famhx__dep__moth__fath_indicator( data, name = "mh_p_famhx__dep__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__dep__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__dep__moth__fath_score
(Family History [Parent] (Depression) Endorsed: Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__dep__moth__fath_score compute_mh_p_famhx__dep__moth__fath_score( data, name = "mh_p_famhx__dep__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__dep__moth__fath_score compute_mh_p_famhx__dep__moth__fath_score( data, name = "mh_p_famhx__dep__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__dep__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__doc__moth__fath_indicator
(Family History [Parent] (Doctor Visit)) Endorsed:
Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__doc__moth__fath_indicator compute_mh_p_famhx__doc__moth__fath_indicator( data, name = "mh_p_famhx__doc__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__doc__moth__fath_indicator compute_mh_p_famhx__doc__moth__fath_indicator( data, name = "mh_p_famhx__doc__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__doc__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__doc__moth__fath_score
(Family History [Parent] (Doctor Visit) Endorsed:
Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__doc__moth__fath_score compute_mh_p_famhx__doc__moth__fath_score( data, name = "mh_p_famhx__doc__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__doc__moth__fath_score compute_mh_p_famhx__doc__moth__fath_score( data, name = "mh_p_famhx__doc__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__doc__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__drg__moth__fath_indicator
(Family History [Parent] (Drug Use) Endorsed: Either parent)
Notes:
Following values are recoded as NA prior to any computation
777
888
999
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__drg__moth__fath_indicator compute_mh_p_famhx__drg__moth__fath_indicator( data, name = "mh_p_famhx__drg__moth__fath_indicator", combine = TRUE )vars_mh_p_famhx__drg__moth__fath_indicator compute_mh_p_famhx__drg__moth__fath_indicator( data, name = "mh_p_famhx__drg__moth__fath_indicator", combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__drg__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__drg__moth__fath_score
(Family History [Parent] (Drug Use) Endorsed: Parents overall)
Notes:
Following values are recoded as NA prior to any computation
777
888
999
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__drg__moth__fath_score compute_mh_p_famhx__drg__moth__fath_score( data, name = "mh_p_famhx__drg__moth__fath_score", combine = TRUE )vars_mh_p_famhx__drg__moth__fath_score compute_mh_p_famhx__drg__moth__fath_score( data, name = "mh_p_famhx__drg__moth__fath_score", combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__drg__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__halluc__moth__fath_indicator
(Family History [Parent] (Hallucinations) Endorsed: Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__halluc__moth__fath_indicator compute_mh_p_famhx__halluc__moth__fath_indicator( data, name = "mh_p_famhx__halluc__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__halluc__moth__fath_indicator compute_mh_p_famhx__halluc__moth__fath_indicator( data, name = "mh_p_famhx__halluc__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__halluc__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__halluc__moth__fath_score
(Family History [Parent] (Hallucinations) Endorsed: Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__halluc__moth__fath_score compute_mh_p_famhx__halluc__moth__fath_score( data, name = "mh_p_famhx__halluc__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__halluc__moth__fath_score compute_mh_p_famhx__halluc__moth__fath_score( data, name = "mh_p_famhx__halluc__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__halluc__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__hosp__moth__fath_indicator
(Family History [Parent] (Hospitalized)) Endorsed:
Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__hosp__moth__fath_indicator compute_mh_p_famhx__hosp__moth__fath_indicator( data, name = "mh_p_famhx__hosp__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__hosp__moth__fath_indicator compute_mh_p_famhx__hosp__moth__fath_indicator( data, name = "mh_p_famhx__hosp__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__hosp__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__hosp__moth__fath_score
(Family History [Parent] (Hospitalized) Endorsed:
Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__hosp__moth__fath_score compute_mh_p_famhx__hosp__moth__fath_score( data, name = "mh_p_famhx__hosp__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__hosp__moth__fath_score compute_mh_p_famhx__hosp__moth__fath_score( data, name = "mh_p_famhx__hosp__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__hosp__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__mania__moth__fath_indicator
(Family History [Parent] (Mania) Endorsed: Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__mania__moth__fath_indicator compute_mh_p_famhx__mania__moth__fath_indicator( data, name = "mh_p_famhx__mania__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__mania__moth__fath_indicator compute_mh_p_famhx__mania__moth__fath_indicator( data, name = "mh_p_famhx__mania__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__mania__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__mania__moth__fath_score
(Family History [Parent] (Mania) Endorsed: Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__mania__moth__fath_score compute_mh_p_famhx__mania__moth__fath_score( data, name = "mh_p_famhx__mania__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__mania__moth__fath_score compute_mh_p_famhx__mania__moth__fath_score( data, name = "mh_p_famhx__mania__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__mania__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__nerve__moth__fath_indicator
(Family History [Parent] (Nerves/Nervous Breakdown) Endorsed:
Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__nerve__moth__fath_indicator compute_mh_p_famhx__nerve__moth__fath_indicator( data, name = "mh_p_famhx__nerve__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__nerve__moth__fath_indicator compute_mh_p_famhx__nerve__moth__fath_indicator( data, name = "mh_p_famhx__nerve__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__nerve__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__nerve__moth__fath_score
(Family History [Parent] (Nerves/Nervous Breakdown) Endorsed:
Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__nerve__moth__fath_score compute_mh_p_famhx__nerve__moth__fath_score( data, name = "mh_p_famhx__nerve__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__nerve__moth__fath_score compute_mh_p_famhx__nerve__moth__fath_score( data, name = "mh_p_famhx__nerve__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__nerve__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__suic__moth__fath_indicator
(Family History [Parent] (Suicide)) Endorsed:
Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__suic__moth__fath_indicator compute_mh_p_famhx__suic__moth__fath_indicator( data, name = "mh_p_famhx__suic__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__suic__moth__fath_indicator compute_mh_p_famhx__suic__moth__fath_indicator( data, name = "mh_p_famhx__suic__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__suic__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__suic__moth__fath_score
(Family History [Parent] (Suicide) Endorsed:
Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__suic__moth__fath_score compute_mh_p_famhx__suic__moth__fath_score( data, name = "mh_p_famhx__suic__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__suic__moth__fath_score compute_mh_p_famhx__suic__moth__fath_score( data, name = "mh_p_famhx__suic__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__suic__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__troub__moth__fath_indicator
(Family History [Parent] (Trouble/Problems) Endorsed: Either parent)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed yes OR mother endorsed yes = 1
father endorsed no AND mother endorsed no = 0
all other cases set to NA
vars_mh_p_famhx__troub__moth__fath_indicator compute_mh_p_famhx__troub__moth__fath_indicator( data, name = "mh_p_famhx__troub__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__troub__moth__fath_indicator compute_mh_p_famhx__troub__moth__fath_indicator( data, name = "mh_p_famhx__troub__moth__fath_indicator", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of fields used to compute
mh_p_famhx__troub__moth__fath_indicator.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_famhx__troub__moth__fath_score
(Family History [Parent] (Trouble/Problems) Endorsed:
Parents overall)
Excluded values:
777
888
999
Notes:
Following logic is applied to compute the score:
father endorsed no AND mother endorsed no = 0
father endorsed yes AND mother endorsed no = 1
father endorsed no AND mother endorsed yes = 2
father endorsed yes AND mother endorsed yes = 3
father endorsed NA AND mother endorsed yes = 4
father endorsed yes AND mother endorsed NA = 5
all other cases set to NA
vars_mh_p_famhx__troub__moth__fath_score compute_mh_p_famhx__troub__moth__fath_score( data, name = "mh_p_famhx__troub__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )vars_mh_p_famhx__troub__moth__fath_score compute_mh_p_famhx__troub__moth__fath_score( data, name = "mh_p_famhx__troub__moth__fath_score", exclude = c("777", "888", "999"), combine = TRUE )
data |
tibble. A data frame containing the data. |
name |
character. The name of the output column for the computed score. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. Whether to combine the summary score column with the
input data frame (Default: |
a character vector of base name of the check boxes used to compute
mh_p_famhx__troub__moth__fath_score.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_gbi_nm
Parent General Behavior Inventory [Parent]: Number missing
Summarized variables:
mh_p_gbi_001
mh_p_gbi_002
mh_p_gbi_003
mh_p_gbi_004
mh_p_gbi_005
mh_p_gbi_006
mh_p_gbi_007
mh_p_gbi_008
mh_p_gbi_009
mh_p_gbi_010
Excluded values: none
vars_mh_p_gbi compute_mh_p_gbi_nm(data, name = "mh_p_gbi_nm", exclude = NULL, combine = TRUE)vars_mh_p_gbi compute_mh_p_gbi_nm(data, name = "mh_p_gbi_nm", exclude = NULL, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_gbi is vector of all column names
used to compute summary score of mh_p_gbi scores.
tbl. see combine.
## Not run: compute_mh_p_gbi_nm(data) |> select( any_of(c("mh_p_gbi_nm", vars_mh_p_gbi)) ) ## End(Not run)## Not run: compute_mh_p_gbi_nm(data) |> select( any_of(c("mh_p_gbi_nm", vars_mh_p_gbi)) ) ## End(Not run)
Computes the summary score mh_p_ksads__adhd__past__sx_mean
KSADS - Attention-Deficit/Hyperactivity Disorder [Parent] (Symptom - Past):
Mean [Validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__adhd__avoid__task__past_sx
mh_p_ksads__adhd__blurt__past_sx
mh_p_ksads__adhd__distract__1schlyr__past_sx
mh_p_ksads__adhd__fidget__past_sx
mh_p_ksads__adhd__flwinstr__past_sx
mh_p_ksads__adhd__forget__past_sx
mh_p_ksads__adhd__hypractv__past_sx
mh_p_ksads__adhd__impuls__past_sx
mh_p_ksads__adhd__interrupt__past_sx
mh_p_ksads__adhd__loses__past_sx
mh_p_ksads__adhd__mistake__past_sx
mh_p_ksads__adhd__motor__past_sx
mh_p_ksads__adhd__notlisten__past_sx
mh_p_ksads__adhd__orgtask__past_sx
mh_p_ksads__adhd__quiet__past_sx
mh_p_ksads__adhd__seat__1schlyr__past_sx
mh_p_ksads__adhd__sustattn__1schlyr__past_sx
mh_p_ksads__adhd__talkexcess__past_sx
mh_p_ksads__adhd__wait__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 19 items missing
vars_mh_p_ksads__adhd__past__sx compute_mh_p_ksads__adhd__past__sx_mean( data, name = "mh_p_ksads__adhd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__adhd__past__sx compute_mh_p_ksads__adhd__past__sx_mean( data, name = "mh_p_ksads__adhd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__adhd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__adhd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__adhd__pres__sx_mean
KSADS - Attention-Deficit/Hyperactivity Disorder [Parent]
(Symptom - Present): Mean [Validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__adhd__avoid__task__pres_sx
mh_p_ksads__adhd__blurt__pres_sx
mh_p_ksads__adhd__distract__grdschl__pres_sx
mh_p_ksads__adhd__fidget__pres_sx
mh_p_ksads__adhd__flwinstr__pres_sx
mh_p_ksads__adhd__forget__pres_sx
mh_p_ksads__adhd__hypractv__pres_sx
mh_p_ksads__adhd__impuls__pres_sx
mh_p_ksads__adhd__interrupt__pres_sx
mh_p_ksads__adhd__loses__pres_sx
mh_p_ksads__adhd__mistake__pres_sx
mh_p_ksads__adhd__motor__pres_sx
mh_p_ksads__adhd__notlisten__pres_sx
mh_p_ksads__adhd__orgtask__pres_sx
mh_p_ksads__adhd__quiet__pres_sx
mh_p_ksads__adhd__seat__grdschl__pres_sx
mh_p_ksads__adhd__sustattn__grdschl__pres_sx
mh_p_ksads__adhd__talkexcess__pres_sx
mh_p_ksads__adhd__wait__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 19 items missing
vars_mh_p_ksads__adhd__pres__sx compute_mh_p_ksads__adhd__pres__sx_mean( data, name = "mh_p_ksads__adhd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__adhd__pres__sx compute_mh_p_ksads__adhd__pres__sx_mean( data, name = "mh_p_ksads__adhd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__adhd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__adhd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__agor__past__sx_mean
KSADS - Agoraphobia [Parent] (Symptom - Past): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__agor__avoid__past_sx
mh_p_ksads__agor__multi__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__agor__past__sx compute_mh_p_ksads__agor__past__sx_mean( data, name = "mh_p_ksads__agor__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__agor__past__sx compute_mh_p_ksads__agor__past__sx_mean( data, name = "mh_p_ksads__agor__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__agor__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__agor__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__agor__pres__sx_mean
KSADS - Agoraphobia [Parent] (Symptom - Present): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__agor__avoid__pres_sx
mh_p_ksads__agor__multi__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__agor__pres__sx compute_mh_p_ksads__agor__pres__sx_mean( data, name = "mh_p_ksads__agor__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__agor__pres__sx compute_mh_p_ksads__agor__pres__sx_mean( data, name = "mh_p_ksads__agor__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__agor__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__agor__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__asd__past__sx_mean
KSADS - Autism Spectrum Disorders [Parent] (Symptom - Past): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__asd__hyporeact__past_sx
mh_p_ksads__asd__hyprreact__past_sx
mh_p_ksads__asd__pooreyecont__past_sx
mh_p_ksads__asd__relatsh__past_sx
mh_p_ksads__asd__restrctintrst__past_sx
mh_p_ksads__asd__routine__past_sx
mh_p_ksads__asd__socemotrcp__past_sx
mh_p_ksads__asd__unusmvmnt__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__asd__past__sx compute_mh_p_ksads__asd__past__sx_mean( data, name = "mh_p_ksads__asd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__asd__past__sx compute_mh_p_ksads__asd__past__sx_mean( data, name = "mh_p_ksads__asd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__asd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__asd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__asd__pres__sx_mean
KSADS - Autism Spectrum Disorders [Parent] (Symptom - Present): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__asd__hyporeact__pres_sx
mh_p_ksads__asd__hyprreact__pres_sx
mh_p_ksads__asd__pooreyecont__pres_sx
mh_p_ksads__asd__relatsh__pres_sx
mh_p_ksads__asd__restrctintrst__pres_sx
mh_p_ksads__asd__routine__pres_sx
mh_p_ksads__asd__socemotrcp__pres_sx
mh_p_ksads__asd__unusmvmnt__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__asd__pres__sx compute_mh_p_ksads__asd__pres__sx_mean( data, name = "mh_p_ksads__asd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__asd__pres__sx compute_mh_p_ksads__asd__pres__sx_mean( data, name = "mh_p_ksads__asd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__asd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__asd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__bpd__past__sx_mean
KSADS - Bipolar Disorders [Parent] (Symptom - Past): Mean
[validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__bpd__distract__incr__past_sx
mh_p_ksads__bpd__distract__past_sx
mh_p_ksads__bpd__enrg__incr__past_sx
mh_p_ksads__bpd__flgtid__past_sx
mh_p_ksads__bpd__goaldir__incr__past_sx
mh_p_ksads__bpd__grndios__past_sx
mh_p_ksads__bpd__hyprsex__past_sx
mh_p_ksads__bpd__irrit__expl__past_sx
mh_p_ksads__bpd__irrit__manic__past_sx
mh_p_ksads__bpd__mood__elv__past_sx
mh_p_ksads__bpd__mood__euph__past_sx
mh_p_ksads__bpd__prspch__past_sx
mh_p_ksads__bpd__psymot__agit__past_sx
mh_p_ksads__bpd__ractho__past_sx
mh_p_ksads__bpd__riskactv__past_sx
mh_p_ksads__bpd__slpdecr__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 16 items missing
vars_mh_p_ksads__bpd__past__sx compute_mh_p_ksads__bpd__past__sx_mean( data, name = "mh_p_ksads__bpd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__bpd__past__sx compute_mh_p_ksads__bpd__past__sx_mean( data, name = "mh_p_ksads__bpd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__bpd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__bpd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__bpd__pres__sx_mean
KSADS - Bipolar Disorders [Parent] (Symptom - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__bpd__distract__incr__pres_sx
mh_p_ksads__bpd__distract__pres_sx
mh_p_ksads__bpd__enrg__incr__pres_sx
mh_p_ksads__bpd__flgtid__pres_sx
mh_p_ksads__bpd__goaldir__incr__pres_sx
mh_p_ksads__bpd__grndios__pres_sx
mh_p_ksads__bpd__hyprsex__pres_sx
mh_p_ksads__bpd__irrit__expl__pres_sx
mh_p_ksads__bpd__irrit__manic__pres_sx
mh_p_ksads__bpd__mood__elv__pres_sx
mh_p_ksads__bpd__mood__euph__pres_sx
mh_p_ksads__bpd__prspch__pres_sx
mh_p_ksads__bpd__psymot__agit__pres_sx
mh_p_ksads__bpd__ractho__pres_sx
mh_p_ksads__bpd__riskactv__pres_sx
mh_p_ksads__bpd__slpdecr__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 16 items missing
vars_mh_p_ksads__bpd__pres__sx compute_mh_p_ksads__bpd__pres__sx_mean( data, name = "mh_p_ksads__bpd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__bpd__pres__sx compute_mh_p_ksads__bpd__pres__sx_mean( data, name = "mh_p_ksads__bpd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__bpd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__bpd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__cond__past__sx_mean
KSADS - Conduct Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 2 missing or declined]
Summarized variables:
mh_p_ksads__cond__breakin__past_sx
mh_p_ksads__cond__bully__past_sx
mh_p_ksads__cond__fight__past_sx
mh_p_ksads__cond__fire__past_sx
mh_p_ksads__cond__lies__past_sx
mh_p_ksads__cond__outlate__past_sx
mh_p_ksads__cond__physcruel__anml__past_sx
mh_p_ksads__cond__physcruel__ppl__past_sx
mh_p_ksads__cond__rob__past_sx
mh_p_ksads__cond__runaway__past_sx
mh_p_ksads__cond__steal__past_sx
mh_p_ksads__cond__truant__past_sx
mh_p_ksads__cond__vandal__past_sx
mh_p_ksads__cond__weapon__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_mh_p_ksads__cond__past__sx compute_mh_p_ksads__cond__past__sx_mean( data, name = "mh_p_ksads__cond__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__cond__past__sx compute_mh_p_ksads__cond__past__sx_mean( data, name = "mh_p_ksads__cond__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__cond__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__cond__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__cond__pres__sx_mean
KSADS - Conduct Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 2 missing or declined]
Summarized variables:
mh_p_ksads__cond__breakin__pres_sx
mh_p_ksads__cond__bully__pres_sx
mh_p_ksads__cond__fight__pres_sx
mh_p_ksads__cond__fire__pres_sx
mh_p_ksads__cond__lies__pres_sx
mh_p_ksads__cond__outlate__pres_sx
mh_p_ksads__cond__physcruel__anml__pres_sx
mh_p_ksads__cond__physcruel__ppl__pres_sx
mh_p_ksads__cond__rob__pres_sx
mh_p_ksads__cond__runaway__pres_sx
mh_p_ksads__cond__steal__pres_sx
mh_p_ksads__cond__truant__pres_sx
mh_p_ksads__cond__vandal__pres_sx
mh_p_ksads__cond__weapon__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_mh_p_ksads__cond__pres__sx compute_mh_p_ksads__cond__pres__sx_mean( data, name = "mh_p_ksads__cond__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__cond__pres__sx compute_mh_p_ksads__cond__pres__sx_mean( data, name = "mh_p_ksads__cond__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__cond__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__cond__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__dep__past__sx_mean
KSADS - Depressive Disorders [Parent] (Symptom - Past): Mean
[validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__dep__anhed__past_sx
mh_p_ksads__dep__appdecr__past_sx
mh_p_ksads__dep__conc__past_sx
mh_p_ksads__dep__fatig__past_sx
mh_p_ksads__dep__glt__past_sx
mh_p_ksads__dep__hplss__past_sx
mh_p_ksads__dep__hyprsom__past_sx
mh_p_ksads__dep__incapp__past_sx
mh_p_ksads__dep__indec__past_sx
mh_p_ksads__dep__insom__past_sx
mh_p_ksads__dep__irrit__past_sx
mh_p_ksads__dep__mood__past_sx
mh_p_ksads__dep__psymot__agit__past_sx
mh_p_ksads__dep__psymot__rtrd__past_sx
mh_p_ksads__dep__slfestmdecr__past_sx
mh_p_ksads__dep__wghtgain__past_sx
mh_p_ksads__dep__wghtloss__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 17 items missing
vars_mh_p_ksads__dep__past__sx compute_mh_p_ksads__dep__past__sx_mean( data, name = "mh_p_ksads__dep__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__dep__past__sx compute_mh_p_ksads__dep__past__sx_mean( data, name = "mh_p_ksads__dep__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__dep__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__dep__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__dep__pres__sx_mean
KSADS - Depressive Disorders [Parent] (Symptom - Present): Mean
[validation: No more than 3 missing or declined]
Summarized variables:
mh_p_ksads__dep__anhed__pres_sx
mh_p_ksads__dep__appdecr__pres_sx
mh_p_ksads__dep__conc__pres_sx
mh_p_ksads__dep__fatig__pres_sx
mh_p_ksads__dep__glt__pres_sx
mh_p_ksads__dep__hplss__pres_sx
mh_p_ksads__dep__hyprsom__pres_sx
mh_p_ksads__dep__incapp__pres_sx
mh_p_ksads__dep__indec__pres_sx
mh_p_ksads__dep__irrit__pres_sx
mh_p_ksads__dep__mood__pres_sx
mh_p_ksads__dep__psymot__agit__pres_sx
mh_p_ksads__dep__psymot__rtrd__pres_sx
mh_p_ksads__dep__slfestmdecr__pres_sx
mh_p_ksads__dep__wghtgain__pres_sx
mh_p_ksads__dep__wghtloss__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 17 items missing
vars_mh_p_ksads__dep__pres__sx compute_mh_p_ksads__dep__pres__sx_mean( data, name = "mh_p_ksads__dep__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__dep__pres__sx compute_mh_p_ksads__dep__pres__sx_mean( data, name = "mh_p_ksads__dep__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__dep__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__dep__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__dmdd__sx_mean
KSADS - Disruptive Mood Dysregulation Disorder [Parent] (Symptom): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__dmdd__outbrst__3perwk_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_p_ksads__dmdd__sx compute_mh_p_ksads__dmdd__sx_mean( data, name = "mh_p_ksads__dmdd__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__dmdd__sx compute_mh_p_ksads__dmdd__sx_mean( data, name = "mh_p_ksads__dmdd__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__dmdd__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__dmdd__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ed__past__sx_mean
KSADS - Eating Disorders [Parent] (Symptom - Past): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__ed__binge__distrs__past_sx
mh_p_ksads__ed__binge__past_sx
mh_p_ksads__ed__compbehav__past_sx
mh_p_ksads__ed__emac__past_sx
mh_p_ksads__ed__fear__obese__past_sx
mh_p_ksads__ed__slfwrth__past_sx
mh_p_ksads__ed__wghtcntrl__oth__past_sx
mh_p_ksads__ed__wghtcntrl__vom__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__ed__past__sx compute_mh_p_ksads__ed__past__sx_mean( data, name = "mh_p_ksads__ed__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ed__past__sx compute_mh_p_ksads__ed__past__sx_mean( data, name = "mh_p_ksads__ed__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ed__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ed__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ed__pres__sx_mean
KSADS - Eating Disorders [Parent] (Symptom - Present): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__ed__binge__distrs__pres_sx
mh_p_ksads__ed__binge__pres_sx
mh_p_ksads__ed__compbehav__pres_sx
mh_p_ksads__ed__emac__pres_sx
mh_p_ksads__ed__fear__obese__pres_sx
mh_p_ksads__ed__slfwrth__pres_sx
mh_p_ksads__ed__wghtcntrl__oth__pres_sx
mh_p_ksads__ed__wghtcntrl__vom__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__ed__pres__sx compute_mh_p_ksads__ed__pres__sx_mean( data, name = "mh_p_ksads__ed__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ed__pres__sx compute_mh_p_ksads__ed__pres__sx_mean( data, name = "mh_p_ksads__ed__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ed__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ed__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__gad__past__sx_mean
KSADS - Generalized Anxiety Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__gad__worry__6mo__past_sx
mh_p_ksads__gad__worry__diffctrl__past_sx
mh_p_ksads__gad__worry__excess__past_sx
mh_p_ksads__gad__worry__multi__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_p_ksads__gad__past__sx compute_mh_p_ksads__gad__past__sx_mean( data, name = "mh_p_ksads__gad__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__gad__past__sx compute_mh_p_ksads__gad__past__sx_mean( data, name = "mh_p_ksads__gad__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__gad__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__gad__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__gad__pres__sx_mean
KSADS - Generalized Anxiety Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__gad__worry__6mo__pres_sx
mh_p_ksads__gad__worry__diffctrl__pres_sx
mh_p_ksads__gad__worry__excess__pres_sx
mh_p_ksads__gad__worry__multi__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_p_ksads__gad__pres__sx compute_mh_p_ksads__gad__pres__sx_mean( data, name = "mh_p_ksads__gad__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__gad__pres__sx compute_mh_p_ksads__gad__pres__sx_mean( data, name = "mh_p_ksads__gad__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__gad__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__gad__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__hom__past__sx_mean
KSADS - Homicidality [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__hom__idea__past_sx
mh_p_ksads__hom__plan__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__hom__past__sx compute_mh_p_ksads__hom__past__sx_mean( data, name = "mh_p_ksads__hom__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__hom__past__sx compute_mh_p_ksads__hom__past__sx_mean( data, name = "mh_p_ksads__hom__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__hom__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__hom__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__hom__pres__sx_mean
KSADS - Homicidality [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__hom__idea__pres_sx
mh_p_ksads__hom__plan__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__hom__pres__sx compute_mh_p_ksads__hom__pres__sx_mean( data, name = "mh_p_ksads__hom__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__hom__pres__sx compute_mh_p_ksads__hom__pres__sx_mean( data, name = "mh_p_ksads__hom__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__hom__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__hom__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ocd__past__sx_mean
KSADS - Obsessive Compulsive Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__ocd__compuls__past_sx
mh_p_ksads__ocd__compuls__prvntanx__past_sx
mh_p_ksads__ocd__compuls__tcnsm__past_sx
mh_p_ksads__ocd__obsess__intru__past_sx
mh_p_ksads__ocd__obsess__past_sx
mh_p_ksads__ocd__obsess__tcnsm__past_sx
mh_p_ksads__ocd__suprstho__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_ksads__ocd__past__sx compute_mh_p_ksads__ocd__past__sx_mean( data, name = "mh_p_ksads__ocd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ocd__past__sx compute_mh_p_ksads__ocd__past__sx_mean( data, name = "mh_p_ksads__ocd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ocd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ocd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ocd__pres__sx_mean
KSADS - Obsessive Compulsive Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__ocd__compuls__pres_sx
mh_p_ksads__ocd__compuls__prvntanx__pres_sx
mh_p_ksads__ocd__compuls__tcnsm__pres_sx
mh_p_ksads__ocd__obsess__intru__pres_sx
mh_p_ksads__ocd__obsess__pres_sx
mh_p_ksads__ocd__obsess__tcnsm__pres_sx
mh_p_ksads__ocd__suprstho__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_ksads__ocd__pres__sx compute_mh_p_ksads__ocd__pres__sx_mean( data, name = "mh_p_ksads__ocd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ocd__pres__sx compute_mh_p_ksads__ocd__pres__sx_mean( data, name = "mh_p_ksads__ocd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ocd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ocd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__odd__past__sx_mean
KSADS - Oppositional Defiant Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__odd__angry__past_sx
mh_p_ksads__odd__argue__past_sx
mh_p_ksads__odd__blame__past_sx
mh_p_ksads__odd__delibannoy__past_sx
mh_p_ksads__odd__disobey__past_sx
mh_p_ksads__odd__temper__past_sx
mh_p_ksads__odd__touchy__past_sx
mh_p_ksads__odd__vindict__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__odd__past__sx compute_mh_p_ksads__odd__past__sx_mean( data, name = "mh_p_ksads__odd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__odd__past__sx compute_mh_p_ksads__odd__past__sx_mean( data, name = "mh_p_ksads__odd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__odd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__odd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__odd__pres__sx_mean
KSADS - Oppositional Defiant Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__odd__angry__pres_sx
mh_p_ksads__odd__argue__pres_sx
mh_p_ksads__odd__blame__pres_sx
mh_p_ksads__odd__delibannoy__pres_sx
mh_p_ksads__odd__disobey__pres_sx
mh_p_ksads__odd__temper__pres_sx
mh_p_ksads__odd__touchy__pres_sx
mh_p_ksads__odd__vindict__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__odd__pres__sx compute_mh_p_ksads__odd__pres__sx_mean( data, name = "mh_p_ksads__odd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__odd__pres__sx compute_mh_p_ksads__odd__pres__sx_mean( data, name = "mh_p_ksads__odd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__odd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__odd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__panic__past__sx_mean
KSADS - Panic Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__panic__attack__maladp__past_sx
mh_p_ksads__panic__attack__past_sx
mh_p_ksads__panic__sympt__past_sx
mh_p_ksads__panic__worry__attack__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_p_ksads__panic__past__sx compute_mh_p_ksads__panic__past__sx_mean( data, name = "mh_p_ksads__panic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__panic__past__sx compute_mh_p_ksads__panic__past__sx_mean( data, name = "mh_p_ksads__panic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__panic__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__panic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__panic__pres__sx_mean
KSADS - Panic Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__panic__attack__maladp__pres_sx
mh_p_ksads__panic__attack__pres_sx
mh_p_ksads__panic__sympt__pres_sx
mh_p_ksads__panic__worry__attack__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_p_ksads__panic__pres__sx compute_mh_p_ksads__panic__pres__sx_mean( data, name = "mh_p_ksads__panic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__panic__pres__sx compute_mh_p_ksads__panic__pres__sx_mean( data, name = "mh_p_ksads__panic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__panic__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__panic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__phobia__past__sx_mean
KSADS - Specific Phobia [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__phobia__avoid__past_sx
mh_p_ksads__phobia__fear__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__phobia__past__sx compute_mh_p_ksads__phobia__past__sx_mean( data, name = "mh_p_ksads__phobia__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__phobia__past__sx compute_mh_p_ksads__phobia__past__sx_mean( data, name = "mh_p_ksads__phobia__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__phobia__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__phobia__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__phobia__pres__sx_mean
KSADS - Specific Phobia [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__phobia__avoid__pres_sx
mh_p_ksads__phobia__fear__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__phobia__pres__sx compute_mh_p_ksads__phobia__pres__sx_mean( data, name = "mh_p_ksads__phobia__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__phobia__pres__sx compute_mh_p_ksads__phobia__pres__sx_mean( data, name = "mh_p_ksads__phobia__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__phobia__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__phobia__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__psych__past__sx_mean
KSADS - Psychosis [Parent] (Symptom - Past): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__psych__delus__oth__past_sx
mh_p_ksads__psych__delus__persec__past_sx
mh_p_ksads__psych__delus__past_sx
mh_p_ksads__psych__halluc__adt__past_sx
mh_p_ksads__psych__halluc__clust__past_sx
mh_p_ksads__psych__halluc__oth__past_sx
mh_p_ksads__psych__halluc__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 7 items missing
vars_mh_p_ksads__psych__past__sx compute_mh_p_ksads__psych__past__sx_mean( data, name = "mh_p_ksads__psych__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__psych__past__sx compute_mh_p_ksads__psych__past__sx_mean( data, name = "mh_p_ksads__psych__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__psych__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__psych__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__psych__pres__sx_mean
KSADS - Psychosis [Parent] (Symptom - Present): Mean
[validation: No more than 2 missing or declined]
Summarized variables:
mh_p_ksads__psych__delus__oth__2wk__pres_sx
mh_p_ksads__psych__delus__persec__2wk__pres_sx
mh_p_ksads__psych__delus__pres_sx
mh_p_ksads__psych__disorg__behav__pres_sx
mh_p_ksads__psych__disorg__speech__pres_sx
mh_p_ksads__psych__halluc__adt__pres_sx
mh_p_ksads__psych__halluc__clust__pres_sx
mh_p_ksads__psych__halluc__oth__altw__pres_sx
mh_p_ksads__psych__halluc__oth__ap__pres_sx
mh_p_ksads__psych__halluc__oth__pres_sx
mh_p_ksads__psych__halluc__pres_sx
mh_p_ksads__psych__neg__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 12 items missing
vars_mh_p_ksads__psych__pres__sx compute_mh_p_ksads__psych__pres__sx_mean( data, name = "mh_p_ksads__psych__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__psych__pres__sx compute_mh_p_ksads__psych__pres__sx_mean( data, name = "mh_p_ksads__psych__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__psych__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__psych__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ptsd__past__sx_mean
KSADS - Post-Traumatic Stress Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 4 missing or declined]
Summarized variables:
mh_p_ksads__ptsd__anhed__past_sx
mh_p_ksads__ptsd__avoid__extrmnd__past_sx
mh_p_ksads__ptsd__avoid__trmatho__past_sx
mh_p_ksads__ptsd__concprob__past_sx
mh_p_ksads__ptsd__depersnl__past_sx
mh_p_ksads__ptsd__derealztn__past_sx
mh_p_ksads__ptsd__detach__past_sx
mh_p_ksads__ptsd__distortcog__cause__past_sx
mh_p_ksads__ptsd__distortcog__consq__past_sx
mh_p_ksads__ptsd__emot__neg__past_sx
mh_p_ksads__ptsd__emot__nopos__past_sx
mh_p_ksads__ptsd__extrmnd__distrs__past_sx
mh_p_ksads__ptsd__flshbck__past_sx
mh_p_ksads__ptsd__hyprvigl__past_sx
mh_p_ksads__ptsd__intrmnd__distrs__past_sx
mh_p_ksads__ptsd__irrit__past_sx
mh_p_ksads__ptsd__memloss__past_sx
mh_p_ksads__ptsd__negblf__past_sx
mh_p_ksads__ptsd__nghtmr__past_sx
mh_p_ksads__ptsd__physreact__past_sx
mh_p_ksads__ptsd__rckls__past_sx
mh_p_ksads__ptsd__sleepdistb__past_sx
mh_p_ksads__ptsd__startle__past_sx
mh_p_ksads__ptsd__trmatho__intru__past_sx
Excluded values:
555
Validation criterion: maximally 4 of 24 items missing
vars_mh_p_ksads__ptsd__past__sx compute_mh_p_ksads__ptsd__past__sx_mean( data, name = "mh_p_ksads__ptsd__past__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ptsd__past__sx compute_mh_p_ksads__ptsd__past__sx_mean( data, name = "mh_p_ksads__ptsd__past__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ptsd__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ptsd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__ptsd__pres__sx_mean
KSADS - Post-Traumatic Stress Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 4 missing or declined]
Summarized variables:
mh_p_ksads__ptsd__anhed__pres_sx
mh_p_ksads__ptsd__avoid__extrmnd__pres_sx
mh_p_ksads__ptsd__avoid__trmatho__pres_sx
mh_p_ksads__ptsd__concprob__pres_sx
mh_p_ksads__ptsd__depersnl__pres_sx
mh_p_ksads__ptsd__derealztn__pres_sx
mh_p_ksads__ptsd__detach__pres_sx
mh_p_ksads__ptsd__distortcog__cause__pres_sx
mh_p_ksads__ptsd__distortcog__consq__pres_sx
mh_p_ksads__ptsd__emot__neg__pres_sx
mh_p_ksads__ptsd__emot__nopos__pres_sx
mh_p_ksads__ptsd__extrmnd__distrs__pres_sx
mh_p_ksads__ptsd__flshbck__pres_sx
mh_p_ksads__ptsd__hyprvigl__pres_sx
mh_p_ksads__ptsd__intrmnd__distrs__pres_sx
mh_p_ksads__ptsd__irrit__pres_sx
mh_p_ksads__ptsd__memloss__pres_sx
mh_p_ksads__ptsd__negblf__pres_sx
mh_p_ksads__ptsd__nghtmr__pres_sx
mh_p_ksads__ptsd__physreact__pres_sx
mh_p_ksads__ptsd__rckls__pres_sx
mh_p_ksads__ptsd__sleepdistb__pres_sx
mh_p_ksads__ptsd__startle__pres_sx
mh_p_ksads__ptsd__trmatho__intru__pres_sx
Excluded values:
555
Validation criterion: maximally 4 of 24 items missing
vars_mh_p_ksads__ptsd__pres__sx compute_mh_p_ksads__ptsd__pres__sx_mean( data, name = "mh_p_ksads__ptsd__pres__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__ptsd__pres__sx compute_mh_p_ksads__ptsd__pres__sx_mean( data, name = "mh_p_ksads__ptsd__pres__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__ptsd__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__ptsd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__sepanx__past__sx_mean
KSADS - Separation Anxiety [Parent] (Symptom - Past): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__sepanx__evnt__fear__past_sx
mh_p_ksads__sepanx__fig__harm__past_sx
mh_p_ksads__sepanx__nghtmr__past_sx
mh_p_ksads__sepanx__nofig__fear__past_sx
mh_p_ksads__sepanx__nofig__physympt__past_sx
mh_p_ksads__sepanx__noschl__past_sx
mh_p_ksads__sepanx__nosleep__past_sx
mh_p_ksads__sepanx__sep__distrs__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__sepanx__past__sx compute_mh_p_ksads__sepanx__past__sx_mean( data, name = "mh_p_ksads__sepanx__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__sepanx__past__sx compute_mh_p_ksads__sepanx__past__sx_mean( data, name = "mh_p_ksads__sepanx__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__sepanx__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__sepanx__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__sepanx__pres__sx_mean
KSADS - Separation Anxiety [Parent] (Symptom - Present): Mean
[validation: No more than 1 missing or declined]
Summarized variables:
mh_p_ksads__sepanx__evnt__fear__pres_sx
mh_p_ksads__sepanx__fig__harm__pres_sx
mh_p_ksads__sepanx__nghtmr__pres_sx
mh_p_ksads__sepanx__nofig__fear__pres_sx
mh_p_ksads__sepanx__nofig__physympt__pres_sx
mh_p_ksads__sepanx__noschl__pres_sx
mh_p_ksads__sepanx__nosleep__pres_sx
mh_p_ksads__sepanx__sep__distrs__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_p_ksads__sepanx__pres__sx compute_mh_p_ksads__sepanx__pres__sx_mean( data, name = "mh_p_ksads__sepanx__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__sepanx__pres__sx compute_mh_p_ksads__sepanx__pres__sx_mean( data, name = "mh_p_ksads__sepanx__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__sepanx__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__sepanx__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__sleep__past__sx_mean
KSADS - Sleep Problems [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__sleep__insom__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_p_ksads__sleep__past__sx compute_mh_p_ksads__sleep__past__sx_mean( data, name = "mh_p_ksads__sleep__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__sleep__past__sx compute_mh_p_ksads__sleep__past__sx_mean( data, name = "mh_p_ksads__sleep__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__sleep__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__sleep__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__sleep__pres__sx_mean
KSADS - Sleep Problems [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__sleep__insom__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_p_ksads__sleep__pres__sx compute_mh_p_ksads__sleep__pres__sx_mean( data, name = "mh_p_ksads__sleep__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__sleep__pres__sx compute_mh_p_ksads__sleep__pres__sx_mean( data, name = "mh_p_ksads__sleep__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__sleep__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__sleep__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__socanx__past__sx_mean
KSADS - Social Anxiety Disorder [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__socanx__anx__past_sx
mh_p_ksads__socanx__avoid__past_sx
mh_p_ksads__socanx__fear__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 3 items missing
vars_mh_p_ksads__socanx__past__sx compute_mh_p_ksads__socanx__past__sx_mean( data, name = "mh_p_ksads__socanx__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__socanx__past__sx compute_mh_p_ksads__socanx__past__sx_mean( data, name = "mh_p_ksads__socanx__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__socanx__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__socanx__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__socanx__pres__sx_mean
KSADS - Social Anxiety Disorder [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__socanx__anx__pres_sx
mh_p_ksads__socanx__avoid__pres_sx
mh_p_ksads__socanx__fear__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 3 items missing
vars_mh_p_ksads__socanx__pres__sx compute_mh_p_ksads__socanx__pres__sx_mean( data, name = "mh_p_ksads__socanx__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__socanx__pres__sx compute_mh_p_ksads__socanx__pres__sx_mean( data, name = "mh_p_ksads__socanx__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__socanx__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__socanx__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__suic__past__sx_mean
KSADS - Suicidality [Parent] (Symptom - Past): Mean
[validation: No more than 2 missing or declined]
Summarized variables:
mh_p_ksads__suic__slfinj__past_sx
mh_p_ksads__suic__slfinj__nointnt__past_sx
mh_p_ksads__suic__slfinj__intnt__past_sx
mh_p_ksads__suic__slfinj__psbldie__past_sx
mh_p_ksads__suic__idea__past_sx
mh_p_ksads__suic__intnt__past_sx
mh_p_ksads__suic__mthd__past_sx
mh_p_ksads__suic__plan__past_sx
mh_p_ksads__suic__prep__past_sx
mh_p_ksads__suic__attmpt__past_sx
mh_p_ksads__suic__attmpt__intrpt__past_sx
mh_p_ksads__suic__attmpt__psbldie__past_sx
mh_p_ksads__suic__wishdead__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 13 items missing
vars_mh_p_ksads__suic__past__sx compute_mh_p_ksads__suic__past__sx_mean( data, name = "mh_p_ksads__suic__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__suic__past__sx compute_mh_p_ksads__suic__past__sx_mean( data, name = "mh_p_ksads__suic__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__suic__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__suic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__suic__pres__sx_mean
KSADS - Suicidality [Parent] (Symptom - Present): Mean
[validation: No more than 2 missing or declined]
Summarized variables:
mh_p_ksads__suic__slfinj__pres_sx
mh_p_ksads__suic__slfinj__nointnt__pres_sx
mh_p_ksads__suic__slfinj__intnt__pres_sx
mh_p_ksads__suic__slfinj__psbldie__pres_sx
mh_p_ksads__suic__idea__pres_sx
mh_p_ksads__suic__intnt__pres_sx
mh_p_ksads__suic__mthd__pres_sx
mh_p_ksads__suic__plan__pres_sx
mh_p_ksads__suic__prep__pres_sx
mh_p_ksads__suic__attmpt__pres_sx
mh_p_ksads__suic__attmpt__intrpt__pres_sx
mh_p_ksads__suic__attmpt__psbldie__pres_sx
mh_p_ksads__suic__wishdead__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 13 items missing
vars_mh_p_ksads__suic__pres__sx compute_mh_p_ksads__suic__pres__sx_mean( data, name = "mh_p_ksads__suic__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__suic__pres__sx compute_mh_p_ksads__suic__pres__sx_mean( data, name = "mh_p_ksads__suic__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__suic__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__suic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__tic__past__sx_mean
KSADS - Tic Disorders [Parent] (Symptom - Past): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__tic__mtr__past_sx
mh_p_ksads__tic__phnc__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__tic__past__sx compute_mh_p_ksads__tic__past__sx_mean( data, name = "mh_p_ksads__tic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__tic__past__sx compute_mh_p_ksads__tic__past__sx_mean( data, name = "mh_p_ksads__tic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__tic__past__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__tic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ksads__tic__pres__sx_mean
KSADS - Tic Disorders [Parent] (Symptom - Present): Mean
[validation: No more than 0 missing or declined]
Summarized variables:
mh_p_ksads__tic__mtr__pres_sx
mh_p_ksads__tic__phnc__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 2 items missing
vars_mh_p_ksads__tic__pres__sx compute_mh_p_ksads__tic__pres__sx_mean( data, name = "mh_p_ksads__tic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_p_ksads__tic__pres__sx compute_mh_p_ksads__tic__pres__sx_mean( data, name = "mh_p_ksads__tic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ksads__tic__pres__sx is a character vector
of all column names used to compute summary score of
mh_p_ksads__tic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_p_ple_count
Life Events [Parent] (Events): Count
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
Excluded values:
444
777
999
vars_mh_p_ple vars_mh_p_ple__exp compute_mh_p_ple_count( data, name = "mh_p_ple_count", combine = TRUE, max_na = NULL )vars_mh_p_ple vars_mh_p_ple__exp compute_mh_p_ple_count( data, name = "mh_p_ple_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_p_ple is a character vector of all column names
used to compute summary score of mh_p_ple.
vars_mh_p_ple__exp is a character vector of all column names
used to compute summary score of mh_p_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_sum__v01
Life Events [Parent] (Severity of Good Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
vars_mh_p_ple__exp__v01 compute_mh_p_ple__severity__good_sum__v01( data, name = "mh_p_ple__severity__good_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )vars_mh_p_ple__exp__v01 compute_mh_p_ple__severity__good_sum__v01( data, name = "mh_p_ple__severity__good_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__exp__v01 is a character vector of all column names
used to compute summary score of mh_p_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_sum__v02
Life Events [Parent] (Severity of Good Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
vars_mh_p_ple__exp__v02 compute_mh_p_ple__severity__good_sum__v02( data, name = "mh_p_ple__severity__good_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )vars_mh_p_ple__exp__v02 compute_mh_p_ple__severity__good_sum__v02( data, name = "mh_p_ple__severity__good_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__exp__v02 is a character vector of all column names
used to compute summary score of mh_p_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_sum__v03
Life Events [Parent] (Severity of Good Events): Sum - Version 3 (Year
6 ) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_003
mh_p_ple__exp_004
mh_p_ple__exp_005
mh_p_ple__exp_006
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_009
mh_p_ple__exp_010
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_016
mh_p_ple__exp_017
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_020
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_025
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_029
mh_p_ple__exp_030
mh_p_ple__exp_031
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
vars_mh_p_ple__exp__v03 compute_mh_p_ple__severity__good_sum__v03( data, name = "mh_p_ple__severity__good_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )vars_mh_p_ple__exp__v03 compute_mh_p_ple__severity__good_sum__v03( data, name = "mh_p_ple__severity__good_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__exp__v03 is a character vector of all column names
used to compute summary score of mh_p_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity__good_sum__v04
Life Events [Parent] (Severity of Good Events): Sum - Version 4
(Starting at Year 7) [Validation: No more than 4 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_p_ple__exp_001
mh_p_ple__exp_002
mh_p_ple__exp_007
mh_p_ple__exp_008
mh_p_ple__exp_011
mh_p_ple__exp_012
mh_p_ple__exp_013
mh_p_ple__exp_014
mh_p_ple__exp_015
mh_p_ple__exp_018
mh_p_ple__exp_019
mh_p_ple__exp_021
mh_p_ple__exp_022
mh_p_ple__exp_023
mh_p_ple__exp_024
mh_p_ple__exp_026
mh_p_ple__exp_027
mh_p_ple__exp_028
mh_p_ple__exp_032
mh_p_ple__exp_033
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
vars_mh_p_ple__exp__v04 compute_mh_p_ple__severity__good_sum__v04( data, name = "mh_p_ple__severity__good_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )vars_mh_p_ple__exp__v04 compute_mh_p_ple__severity__good_sum__v04( data, name = "mh_p_ple__severity__good_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
vars_mh_p_ple__exp__v04 is a character vector of all column names
used to compute summary score of mh_p_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_sum
Life Events [Parent] (Severity): Sum [Validation: No more than 5
events missing and no severity items missing or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
vars_mh_p_ple__severity compute_mh_p_ple__severity_sum( data, name = "mh_p_ple__severity_sum", combine = TRUE, max_na = 5 )vars_mh_p_ple__severity compute_mh_p_ple__severity_sum( data, name = "mh_p_ple__severity_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
vars_mh_p_ple__severity is a character vector of all column names
used to compute summary score of mh_p_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_sum__v01
Life Events [Parent] (Severity): Sum - Version 1 (Year 3)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
vars_mh_p_ple__severity__v01 compute_mh_p_ple__severity_sum__v01( data, name = "mh_p_ple__severity_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )vars_mh_p_ple__severity__v01 compute_mh_p_ple__severity_sum__v01( data, name = "mh_p_ple__severity_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__severity__v01 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_sum__v02
Life Events [Parent] (Severity): Sum - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
Excluded values:
444
777
999
Validation criterion: maximally 6 of 32 items missing
vars_mh_p_ple__severity__v02 compute_mh_p_ple__severity_sum__v02( data, name = "mh_p_ple__severity_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )vars_mh_p_ple__severity__v02 compute_mh_p_ple__severity_sum__v02( data, name = "mh_p_ple__severity_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__severity__v02 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_sum__v03
Life Events [Parent] (Severity): Sum - Version 3 (Year 6 )
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_003
mh_p_ple__severity_004
mh_p_ple__severity_005
mh_p_ple__severity_006
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_009
mh_p_ple__severity_010
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_016
mh_p_ple__severity_017
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_020
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_025
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_029
mh_p_ple__severity_030
mh_p_ple__severity_031
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
vars_mh_p_ple__severity__v03 compute_mh_p_ple__severity_sum__v03( data, name = "mh_p_ple__severity_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )vars_mh_p_ple__severity__v03 compute_mh_p_ple__severity_sum__v03( data, name = "mh_p_ple__severity_sum__v03", events = "ses-06A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_p_ple__severity__v03 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple__severity_sum__v04
Life Events [Parent] (Severity): Sum - Version 4 (Starting at Year 7)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_p_ple__severity_001
mh_p_ple__severity_002
mh_p_ple__severity_007
mh_p_ple__severity_008
mh_p_ple__severity_011
mh_p_ple__severity_012
mh_p_ple__severity_013
mh_p_ple__severity_014
mh_p_ple__severity_015
mh_p_ple__severity_018
mh_p_ple__severity_019
mh_p_ple__severity_021
mh_p_ple__severity_022
mh_p_ple__severity_023
mh_p_ple__severity_024
mh_p_ple__severity_026
mh_p_ple__severity_027
mh_p_ple__severity_028
mh_p_ple__severity_032
mh_p_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 4 of 20 items missing
vars_mh_p_ple__severity__v04 compute_mh_p_ple__severity_sum__v04( data, name = "mh_p_ple__severity_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )vars_mh_p_ple__severity__v04 compute_mh_p_ple__severity_sum__v04( data, name = "mh_p_ple__severity_sum__v04", events = "ses-07A", combine = TRUE, max_na = 4 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 4). |
vars_mh_p_ple__severity__v04 is a character vector of all column
names
used to compute summary score of mh_p_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_count__v01
Life Events [Parent] (Events): Count - Version 1 (Year 3)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
Excluded values:
444
777
999
vars_mh_p_ple__v01 compute_mh_p_ple_count__v01( data, name = "mh_p_ple_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )vars_mh_p_ple__v01 compute_mh_p_ple_count__v01( data, name = "mh_p_ple_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_p_ple__v01 is a character vector of all column names
used to compute summary score of mh_p_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_count__v02
Life Events [Parent] (Events): Count - Version 2 (Year 4 and Year 5)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
mh_p_ple_032
Excluded values:
444
777
999
vars_mh_p_ple__v02 compute_mh_p_ple_count__v02( data, name = "mh_p_ple_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )vars_mh_p_ple__v02 compute_mh_p_ple_count__v02( data, name = "mh_p_ple_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_p_ple__v02 is a character vector of all column names
used to compute summary score of mh_p_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_count__v03
Life Events [Parent] (Events): Count - Version 3 (Year 6)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_003
mh_p_ple_004
mh_p_ple_005
mh_p_ple_006
mh_p_ple_007
mh_p_ple_008
mh_p_ple_009
mh_p_ple_010
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_016
mh_p_ple_017
mh_p_ple_018
mh_p_ple_019
mh_p_ple_020
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_025
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_029
mh_p_ple_030
mh_p_ple_031
mh_p_ple_032
mh_p_ple_033
Excluded values:
444
777
999
vars_mh_p_ple__v03 compute_mh_p_ple_count__v03( data, name = "mh_p_ple_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )vars_mh_p_ple__v03 compute_mh_p_ple_count__v03( data, name = "mh_p_ple_count__v03", events = "ses-06A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_p_ple__v03 is a character vector of all column names
used to compute summary score of mh_p_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ple_count__v04
Life Events [Parent] (Events): Count - Version 4 (Starting at Year 7)
Summarized variables:
mh_p_ple_001
mh_p_ple_002
mh_p_ple_007
mh_p_ple_008
mh_p_ple_011
mh_p_ple_012
mh_p_ple_013
mh_p_ple_014
mh_p_ple_015
mh_p_ple_018
mh_p_ple_019
mh_p_ple_021
mh_p_ple_022
mh_p_ple_023
mh_p_ple_024
mh_p_ple_026
mh_p_ple_027
mh_p_ple_028
mh_p_ple_032
mh_p_ple_033
Excluded values:
444
777
999
vars_mh_p_ple__v04 compute_mh_p_ple_count__v04( data, name = "mh_p_ple_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )vars_mh_p_ple__v04 compute_mh_p_ple_count__v04( data, name = "mh_p_ple_count__v04", events = "ses-07A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_p_ple__v04 is a character vector of all column names
used to compute summary score of mh_p_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_p_ssrs_nm
Short Social Responsiveness Scale [Parent]: Number missing
Summarized variables:
mh_p_ssrs_001
mh_p_ssrs_002
mh_p_ssrs_003
mh_p_ssrs_004
mh_p_ssrs_005
mh_p_ssrs_006
mh_p_ssrs_007
mh_p_ssrs_008
mh_p_ssrs_009
mh_p_ssrs_010
mh_p_ssrs_011
Excluded values: none
vars_mh_p_ssrs compute_mh_p_ssrs_nm( data, name = "mh_p_ssrs_nm", exclude = NULL, combine = TRUE )vars_mh_p_ssrs compute_mh_p_ssrs_nm( data, name = "mh_p_ssrs_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_p_ssrs is vector of all column names
used to compute summary score of mh_p_ssrs scores.
tbl. see combine.
## Not run: compute_mh_p_ssrs_nm(data) |> select( any_of(c("mh_p_ssrs_nm", vars_mh_p_ssrs)) ) ## End(Not run)## Not run: compute_mh_p_ssrs_nm(data) |> select( any_of(c("mh_p_ssrs_nm", vars_mh_p_ssrs)) ) ## End(Not run)
Computes the summary score mh_t_bpm_nm
Brief Problem Monitor [Teacher]: Number missing
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
vars_mh_t_bpm compute_mh_t_bpm_nm( data, name = "mh_t_bpm_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_t_bpm compute_mh_t_bpm_nm( data, name = "mh_t_bpm_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_t_bpm is vector of all column names
used to compute summary score of mh_t_bpm scores.
tbl. see combine.
## Not run: compute_mh_t_bpm_nm(data) |> select( any_of(c("mh_t_bpm_nm", vars_mh_t_bpm)) ) ## End(Not run)## Not run: compute_mh_t_bpm_nm(data) |> select( any_of(c("mh_t_bpm_nm", vars_mh_t_bpm)) ) ## End(Not run)
Computes the summary score mh_t_bpm__attn_nm
Brief Problem Monitor [Teacher] (Attention): Number missing
Summarized variables:
mh_t_bpm__attn_001
mh_t_bpm__attn_002
mh_t_bpm__attn_003
mh_t_bpm__attn_004
mh_t_bpm__attn_005
mh_t_bpm__attn_006
Excluded values:
777
999
vars_mh_t_bpm__attn compute_mh_t_bpm__attn_nm( data, name = "mh_t_bpm__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_t_bpm__attn compute_mh_t_bpm__attn_nm( data, name = "mh_t_bpm__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_t_bpm__attn is vector of all column names
used to compute summary score of mh_t_bpm__attn scores.
tbl. see combine.
## Not run: compute_mh_t_bpm__attn_nm(data) |> select( any_of(c("mh_t_bpm__attn_nm", vars_mh_t_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_t_bpm__attn_nm(data) |> select( any_of(c("mh_t_bpm__attn_nm", vars_mh_t_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_t_bpm__ext_nm
Brief Problem Monitor [Teacher] (Externalizing): Number missing
Summarized variables:
mh_t_bpm__ext_001
mh_t_bpm__ext_002
mh_t_bpm__ext_003
mh_t_bpm__ext_004
mh_t_bpm__ext_005
mh_t_bpm__ext_006
Excluded values:
777
999
vars_mh_t_bpm__ext compute_mh_t_bpm__ext_nm( data, name = "mh_t_bpm__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_t_bpm__ext compute_mh_t_bpm__ext_nm( data, name = "mh_t_bpm__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_t_bpm__ext is vector of all column names
used to compute summary score of mh_t_bpm__ext scores.
tbl. see combine.
## Not run: compute_mh_t_bpm__ext_nm(data) |> select( any_of(c("mh_t_bpm__ext_nm", vars_mh_t_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_t_bpm__ext_nm(data) |> select( any_of(c("mh_t_bpm__ext_nm", vars_mh_t_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_t_bpm__int_nm
Brief Problem Monitor [Teacher] (Internalizing): Number missing
Summarized variables:
mh_t_bpm__int_001
mh_t_bpm__int_002
mh_t_bpm__int_003
mh_t_bpm__int_004
mh_t_bpm__int_005
mh_t_bpm__int_006
Excluded values:
777
999
vars_mh_t_bpm__int compute_mh_t_bpm__int_nm( data, name = "mh_t_bpm__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_t_bpm__int compute_mh_t_bpm__int_nm( data, name = "mh_t_bpm__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_t_bpm__int is vector of all column names
used to compute summary score of mh_t_bpm__int scores.
tbl. see combine.
## Not run: compute_mh_t_bpm__int_nm(data) |> select( any_of(c("mh_t_bpm__int_nm", vars_mh_t_bpm__int)) ) ## End(Not run)## Not run: compute_mh_t_bpm__int_nm(data) |> select( any_of(c("mh_t_bpm__int_nm", vars_mh_t_bpm__int)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__dr_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Drive): Number missing
Summarized variables:
mh_y_bisbas__bas__dr_001
mh_y_bisbas__bas__dr_002
mh_y_bisbas__bas__dr_003
mh_y_bisbas__bas__dr_004
Excluded values: none
vars_mh_y_bisbas__bas__dr compute_mh_y_bisbas__bas__dr_nm( data, name = "mh_y_bisbas__bas__dr_nm", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bas__dr compute_mh_y_bisbas__bas__dr_nm( data, name = "mh_y_bisbas__bas__dr_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bas__dr is vector of all column names
used to compute summary score of mh_y_bisbas__bas__dr scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bas__dr_nm(data) |> select( any_of(c("mh_y_bisbas__bas__dr_nm", vars_mh_y_bisbas__bas__dr)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__dr_nm(data) |> select( any_of(c("mh_y_bisbas__bas__dr_nm", vars_mh_y_bisbas__bas__dr)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__fs_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Fun Seeking): Number missing
Summarized variables:
mh_y_bisbas__bas__fs_001
mh_y_bisbas__bas__fs_002
mh_y_bisbas__bas__fs_003
mh_y_bisbas__bas__fs_004
Excluded values: none
vars_mh_y_bisbas__bas__fs compute_mh_y_bisbas__bas__fs_nm( data, name = "mh_y_bisbas__bas__fs_nm", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bas__fs compute_mh_y_bisbas__bas__fs_nm( data, name = "mh_y_bisbas__bas__fs_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bas__fs is vector of all column names
used to compute summary score of mh_y_bisbas__bas__fs scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bas__fs_nm(data) |> select( any_of(c("mh_y_bisbas__bas__fs_nm", vars_mh_y_bisbas__bas__fs)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__fs_nm(data) |> select( any_of(c("mh_y_bisbas__bas__fs_nm", vars_mh_y_bisbas__bas__fs)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__rr_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BAS Reward Responsiveness): Number missing
Summarized variables:
mh_y_bisbas__bas__rr_001
mh_y_bisbas__bas__rr_002
mh_y_bisbas__bas__rr_003
mh_y_bisbas__bas__rr_004
mh_y_bisbas__bas__rr_005
Excluded values: none
vars_mh_y_bisbas__bas__rr compute_mh_y_bisbas__bas__rr_nm( data, name = "mh_y_bisbas__bas__rr_nm", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bas__rr compute_mh_y_bisbas__bas__rr_nm( data, name = "mh_y_bisbas__bas__rr_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bas__rr is vector of all column names
used to compute summary score of mh_y_bisbas__bas__rr scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bas__rr_nm(data) |> select( any_of(c("mh_y_bisbas__bas__rr_nm", vars_mh_y_bisbas__bas__rr)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__rr_nm(data) |> select( any_of(c("mh_y_bisbas__bas__rr_nm", vars_mh_y_bisbas__bas__rr)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bas__rr_nm__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] ((BAS Reward Responsiveness (modified)): Number missing
Summarized variables:
mh_y_bisbas__bas__rr_001
mh_y_bisbas__bas__rr_002
mh_y_bisbas__bas__rr_004
mh_y_bisbas__bas__rr_005
Excluded values: none
vars_mh_y_bisbas__bas__rr__v01 compute_mh_y_bisbas__bas__rr_nm__v01( data, name = "mh_y_bisbas__bas__rr_nm__v01", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bas__rr__v01 compute_mh_y_bisbas__bas__rr_nm__v01( data, name = "mh_y_bisbas__bas__rr_nm__v01", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bas__rr__v01 is vector of all column names
used to compute summary score of mh_y_bisbas__bas__rr__v01 scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bas__rr_nm__v01(data) |> select( any_of(c("mh_y_bisbas__bas__rr_nm__v01", vars_mh_y_bisbas__bas__rr__v01)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bas__rr_nm__v01(data) |> select( any_of(c("mh_y_bisbas__bas__rr_nm__v01", vars_mh_y_bisbas__bas__rr__v01)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bis_nm
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS): Number missing
Summarized variables:
mh_y_bisbas__bis_001
mh_y_bisbas__bis_002
mh_y_bisbas__bis_003
mh_y_bisbas__bis_004
mh_y_bisbas__bis_005
mh_y_bisbas__bis_006
mh_y_bisbas__bis_007
Excluded values: none
vars_mh_y_bisbas__bis compute_mh_y_bisbas__bis_nm( data, name = "mh_y_bisbas__bis_nm", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bis compute_mh_y_bisbas__bis_nm( data, name = "mh_y_bisbas__bis_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bis is vector of all column names
used to compute summary score of mh_y_bisbas__bis scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bis_nm(data) |> select( any_of(c("mh_y_bisbas__bis_nm", vars_mh_y_bisbas__bis)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bis_nm(data) |> select( any_of(c("mh_y_bisbas__bis_nm", vars_mh_y_bisbas__bis)) ) ## End(Not run)
Computes the summary score mh_y_bisbas__bis_nm__v01
The Behavioral Inhibition System/Behavioral Activation System Scales
[Youth] (BIS (modified)): Number missing
Summarized variables:
mh_y_bisbas__bis_002
mh_y_bisbas__bis_003
mh_y_bisbas__bis_004
mh_y_bisbas__bis_006
Excluded values: none
vars_mh_y_bisbas__bis__v01 compute_mh_y_bisbas__bis_nm__v01( data, name = "mh_y_bisbas__bis_nm__v01", exclude = NULL, combine = TRUE )vars_mh_y_bisbas__bis__v01 compute_mh_y_bisbas__bis_nm__v01( data, name = "mh_y_bisbas__bis_nm__v01", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_bisbas__bis__v01 is vector of all column names
used to compute summary score of mh_y_bisbas__bis__v01 scores.
tbl. see combine.
## Not run: compute_mh_y_bisbas__bis_nm__v01(data) |> select( any_of(c("mh_y_bisbas__bis_nm__v01", vars_mh_y_bisbas__bis__v01)) ) ## End(Not run)## Not run: compute_mh_y_bisbas__bis_nm__v01(data) |> select( any_of(c("mh_y_bisbas__bis_nm__v01", vars_mh_y_bisbas__bis__v01)) ) ## End(Not run)
Computes the summary score mh_y_bpm_nm
Brief Problem Monitor [Youth]: Number missing
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
vars_mh_y_bpm compute_mh_y_bpm_nm( data, name = "mh_y_bpm_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_bpm compute_mh_y_bpm_nm( data, name = "mh_y_bpm_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_bpm is vector of all column names
used to compute summary score of mh_y_bpm scores.
tbl. see combine.
## Not run: compute_mh_y_bpm_nm(data) |> select( any_of(c("mh_y_bpm_nm", vars_mh_y_bpm)) ) ## End(Not run)## Not run: compute_mh_y_bpm_nm(data) |> select( any_of(c("mh_y_bpm_nm", vars_mh_y_bpm)) ) ## End(Not run)
Computes the summary score mh_y_bpm__attn_nm
Brief Problem Monitor [Youth] (Attention): Number missing
Summarized variables:
mh_y_bpm__attn_001
mh_y_bpm__attn_002
mh_y_bpm__attn_003
mh_y_bpm__attn_004
mh_y_bpm__attn_005
mh_y_bpm__attn_006
Excluded values:
777
999
vars_mh_y_bpm__attn compute_mh_y_bpm__attn_nm( data, name = "mh_y_bpm__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_bpm__attn compute_mh_y_bpm__attn_nm( data, name = "mh_y_bpm__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_bpm__attn is vector of all column names
used to compute summary score of mh_y_bpm__attn scores.
tbl. see combine.
## Not run: compute_mh_y_bpm__attn_nm(data) |> select( any_of(c("mh_y_bpm__attn_nm", vars_mh_y_bpm__attn)) ) ## End(Not run)## Not run: compute_mh_y_bpm__attn_nm(data) |> select( any_of(c("mh_y_bpm__attn_nm", vars_mh_y_bpm__attn)) ) ## End(Not run)
Computes the summary score mh_y_bpm__ext_nm
Brief Problem Monitor [Youth] (Externalizing): Number missing
Summarized variables:
mh_y_bpm__ext_001
mh_y_bpm__ext_002
mh_y_bpm__ext_003
mh_y_bpm__ext_004
mh_y_bpm__ext_005
mh_y_bpm__ext_006
mh_y_bpm__ext_007
Excluded values:
777
999
vars_mh_y_bpm__ext compute_mh_y_bpm__ext_nm( data, name = "mh_y_bpm__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_bpm__ext compute_mh_y_bpm__ext_nm( data, name = "mh_y_bpm__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_bpm__ext is vector of all column names
used to compute summary score of mh_y_bpm__ext scores.
tbl. see combine.
## Not run: compute_mh_y_bpm__ext_nm(data) |> select( any_of(c("mh_y_bpm__ext_nm", vars_mh_y_bpm__ext)) ) ## End(Not run)## Not run: compute_mh_y_bpm__ext_nm(data) |> select( any_of(c("mh_y_bpm__ext_nm", vars_mh_y_bpm__ext)) ) ## End(Not run)
Computes the summary score mh_y_bpm__int_nm
Brief Problem Monitor [Youth] (Internalizing): Number missing
Summarized variables:
mh_y_bpm__int_001
mh_y_bpm__int_002
mh_y_bpm__int_003
mh_y_bpm__int_004
mh_y_bpm__int_005
mh_y_bpm__int_006
Excluded values:
777
999
vars_mh_y_bpm__int compute_mh_y_bpm__int_nm( data, name = "mh_y_bpm__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_bpm__int compute_mh_y_bpm__int_nm( data, name = "mh_y_bpm__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_bpm__int is vector of all column names
used to compute summary score of mh_y_bpm__int scores.
tbl. see combine.
## Not run: compute_mh_y_bpm__int_nm(data) |> select( any_of(c("mh_y_bpm__int_nm", vars_mh_y_bpm__int)) ) ## End(Not run)## Not run: compute_mh_y_bpm__int_nm(data) |> select( any_of(c("mh_y_bpm__int_nm", vars_mh_y_bpm__int)) ) ## End(Not run)
Computes the summary score mh_y_erq__reapp_mean
Emotion Regulation Questionnaire [Youth] (Reappraisal): Mean
Summarized variables:
mh_y_erq__reapp_001
mh_y_erq__reapp_002
mh_y_erq__reapp_003
Excluded values:
777
Validation criterion: none of 3 items missing
vars_mh_y_erq__reapp compute_mh_y_erq__reapp_mean( data, name = "mh_y_erq__reapp_mean", max_na = 0, exclude = c("777"), combine = TRUE )vars_mh_y_erq__reapp compute_mh_y_erq__reapp_mean( data, name = "mh_y_erq__reapp_mean", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_erq__reapp is vector of all column names
used to compute summary score of mh_y_erq__reapp scores.
tbl. see combine.
## Not run: compute_mh_y_erq__reapp_mean(data) |> select( any_of(c("mh_y_erq__reapp_mean", vars_mh_y_erq__reapp)) ) ## End(Not run)## Not run: compute_mh_y_erq__reapp_mean(data) |> select( any_of(c("mh_y_erq__reapp_mean", vars_mh_y_erq__reapp)) ) ## End(Not run)
Computes the summary score mh_y_erq__suppr_mean
Emotion Regulation Questionnaire [Youth] (Suppression): Mean
Summarized variables:
mh_y_erq__suppr_001
mh_y_erq__suppr_002
mh_y_erq__suppr_003
Excluded values:
777
Validation criterion: none of 3 items missing
vars_mh_y_erq__suppr compute_mh_y_erq__suppr_mean( data, name = "mh_y_erq__suppr_mean", max_na = 0, exclude = c("777"), combine = TRUE )vars_mh_y_erq__suppr compute_mh_y_erq__suppr_mean( data, name = "mh_y_erq__suppr_mean", max_na = 0, exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_erq__suppr is vector of all column names
used to compute summary score of mh_y_erq__suppr scores.
tbl. see combine.
## Not run: compute_mh_y_erq__suppr_mean(data) |> select( any_of(c("mh_y_erq__suppr_mean", vars_mh_y_erq__suppr)) ) ## End(Not run)## Not run: compute_mh_y_erq__suppr_mean(data) |> select( any_of(c("mh_y_erq__suppr_mean", vars_mh_y_erq__suppr)) ) ## End(Not run)
Computes the summary score mh_y_ksads__bpd__past__sx_mean
KSADS - Bipolar Disorders [Youth] (Symptom - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
mh_y_ksads__bpd__distract__incr__past_sx
mh_y_ksads__bpd__distract__past_sx
mh_y_ksads__bpd__enrg__incr__past_sx
mh_y_ksads__bpd__flgtid__past_sx
mh_y_ksads__bpd__goaldir__incr__past_sx
mh_y_ksads__bpd__grndios__past_sx
mh_y_ksads__bpd__hyprsex__past_sx
mh_y_ksads__bpd__irrit__expl__past_sx
mh_y_ksads__bpd__irrit__manic__past_sx
mh_y_ksads__bpd__mood__elv__past_sx
mh_y_ksads__bpd__mood__euph__past_sx
mh_y_ksads__bpd__prspch__past_sx
mh_y_ksads__bpd__psymot__agit__past_sx
mh_y_ksads__bpd__ractho__past_sx
mh_y_ksads__bpd__riskactv__past_sx
mh_y_ksads__bpd__slpdecr__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 16 items missing
vars_mh_y_ksads__bpd__past__sx compute_mh_y_ksads__bpd__past__sx_mean( data, name = "mh_y_ksads__bpd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__bpd__past__sx compute_mh_y_ksads__bpd__past__sx_mean( data, name = "mh_y_ksads__bpd__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__bpd__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__bpd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__bpd__pres__sx_mean
KSADS - Bipolar Disorders [Youth] (Symptom - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
mh_y_ksads__bpd__distract__incr__pres_sx
mh_y_ksads__bpd__distract__pres_sx
mh_y_ksads__bpd__enrg__incr__pres_sx
mh_y_ksads__bpd__flgtid__pres_sx
mh_y_ksads__bpd__goaldir__incr__pres_sx
mh_y_ksads__bpd__grndios__pres_sx
mh_y_ksads__bpd__hyprsex__pres_sx
mh_y_ksads__bpd__irrit__expl__pres_sx
mh_y_ksads__bpd__irrit__manic__pres_sx
mh_y_ksads__bpd__mood__elv__pres_sx
mh_y_ksads__bpd__mood__euph__pres_sx
mh_y_ksads__bpd__prspch__pres_sx
mh_y_ksads__bpd__psymot__agit__pres_sx
mh_y_ksads__bpd__ractho__pres_sx
mh_y_ksads__bpd__riskactv__pres_sx
mh_y_ksads__bpd__slpdecr__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 16 items missing
vars_mh_y_ksads__bpd__pres__sx compute_mh_y_ksads__bpd__pres__sx_mean( data, name = "mh_y_ksads__bpd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__bpd__pres__sx compute_mh_y_ksads__bpd__pres__sx_mean( data, name = "mh_y_ksads__bpd__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__bpd__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__bpd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__cond__past__sx_mean
KSADS - Conduct Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
mh_y_ksads__cond__breakin__past_sx
mh_y_ksads__cond__bully__past_sx
mh_y_ksads__cond__fight__past_sx
mh_y_ksads__cond__fire__past_sx
mh_y_ksads__cond__lies__past_sx
mh_y_ksads__cond__outlate__past_sx
mh_y_ksads__cond__physcruel__anml__past_sx
mh_y_ksads__cond__physcruel__ppl__past_sx
mh_y_ksads__cond__rob__past_sx
mh_y_ksads__cond__runaway__past_sx
mh_y_ksads__cond__steal__past_sx
mh_y_ksads__cond__truant__past_sx
mh_y_ksads__cond__vandal__past_sx
mh_y_ksads__cond__weapon__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_mh_y_ksads__cond__past__sx compute_mh_y_ksads__cond__past__sx_mean( data, name = "mh_y_ksads__cond__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__cond__past__sx compute_mh_y_ksads__cond__past__sx_mean( data, name = "mh_y_ksads__cond__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__cond__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__cond__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__cond__pres__sx_mean
KSADS - Conduct Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
mh_y_ksads__cond__breakin__pres_sx
mh_y_ksads__cond__bully__pres_sx
mh_y_ksads__cond__fight__pres_sx
mh_y_ksads__cond__fire__pres_sx
mh_y_ksads__cond__lies__pres_sx
mh_y_ksads__cond__outlate__pres_sx
mh_y_ksads__cond__physcruel__anml__pres_sx
mh_y_ksads__cond__physcruel__ppl__pres_sx
mh_y_ksads__cond__rob__pres_sx
mh_y_ksads__cond__runaway__pres_sx
mh_y_ksads__cond__steal__pres_sx
mh_y_ksads__cond__truant__pres_sx
mh_y_ksads__cond__vandal__pres_sx
mh_y_ksads__cond__weapon__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_mh_y_ksads__cond__pres__sx compute_mh_y_ksads__cond__pres__sx_mean( data, name = "mh_y_ksads__cond__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__cond__pres__sx compute_mh_y_ksads__cond__pres__sx_mean( data, name = "mh_y_ksads__cond__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__cond__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__cond__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__dep__past__sx_mean
KSADS - Depressive Disorders [Youth] (Symptom - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
mh_y_ksads__dep__anhed__past_sx
mh_y_ksads__dep__appdecr__past_sx
mh_y_ksads__dep__conc__past_sx
mh_y_ksads__dep__fatig__past_sx
mh_y_ksads__dep__glt__past_sx
mh_y_ksads__dep__hplss__past_sx
mh_y_ksads__dep__hyprsom__past_sx
mh_y_ksads__dep__incapp__past_sx
mh_y_ksads__dep__indec__past_sx
mh_y_ksads__dep__insom__past_sx
mh_y_ksads__dep__irrit__past_sx
mh_y_ksads__dep__mood__past_sx
mh_y_ksads__dep__psymot__agit__past_sx
mh_y_ksads__dep__psymot__rtrd__past_sx
mh_y_ksads__dep__slfestmdecr__past_sx
mh_y_ksads__dep__wghtgain__past_sx
mh_y_ksads__dep__wghtloss__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 17 items missing
vars_mh_y_ksads__dep__past__sx compute_mh_y_ksads__dep__past__sx_mean( data, name = "mh_y_ksads__dep__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__dep__past__sx compute_mh_y_ksads__dep__past__sx_mean( data, name = "mh_y_ksads__dep__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__dep__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__dep__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__dep__pres__sx_mean
KSADS - Depressive Disorders [Youth] (Symptom - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
mh_y_ksads__dep__anhed__pres_sx
mh_y_ksads__dep__appdecr__pres_sx
mh_y_ksads__dep__conc__pres_sx
mh_y_ksads__dep__fatig__pres_sx
mh_y_ksads__dep__glt__pres_sx
mh_y_ksads__dep__hplss__pres_sx
mh_y_ksads__dep__hyprsom__pres_sx
mh_y_ksads__dep__incapp__pres_sx
mh_y_ksads__dep__indec__pres_sx
mh_y_ksads__dep__irrit__pres_sx
mh_y_ksads__dep__mood__pres_sx
mh_y_ksads__dep__psymot__agit__pres_sx
mh_y_ksads__dep__psymot__rtrd__pres_sx
mh_y_ksads__dep__slfestmdecr__pres_sx
mh_y_ksads__dep__wghtgain__pres_sx
mh_y_ksads__dep__wghtloss__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 17 items missing
vars_mh_y_ksads__dep__pres__sx compute_mh_y_ksads__dep__pres__sx_mean( data, name = "mh_y_ksads__dep__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__dep__pres__sx compute_mh_y_ksads__dep__pres__sx_mean( data, name = "mh_y_ksads__dep__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__dep__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__dep__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__dmdd__sx_mean
KSADS - Disruptive Mood Dysregulation Disorder [Youth] (Symptom): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__dmdd__outbrst__3perwk_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_y_ksads__dmdd__sx compute_mh_y_ksads__dmdd__sx_mean( data, name = "mh_y_ksads__dmdd__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__dmdd__sx compute_mh_y_ksads__dmdd__sx_mean( data, name = "mh_y_ksads__dmdd__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__dmdd__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__dmdd__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ed__past__sx_mean
KSADS - Eating Disorders [Youth] (Symptom - Past): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_y_ksads__ed__binge__distrs__past_sx
mh_y_ksads__ed__binge__past_sx
mh_y_ksads__ed__compbehav__past_sx
mh_y_ksads__ed__emac__past_sx
mh_y_ksads__ed__fear__obese__past_sx
mh_y_ksads__ed__slfwrth__past_sx
mh_y_ksads__ed__wghtcntrl__oth__past_sx
mh_y_ksads__ed__wghtcntrl__vom__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_y_ksads__ed__past__sx compute_mh_y_ksads__ed__past__sx_mean( data, name = "mh_y_ksads__ed__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ed__past__sx compute_mh_y_ksads__ed__past__sx_mean( data, name = "mh_y_ksads__ed__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ed__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ed__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ed__pres__sx_mean
KSADS - Eating Disorders [Youth] (Symptom - Present): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_y_ksads__ed__binge__distrs__pres_sx
mh_y_ksads__ed__binge__pres_sx
mh_y_ksads__ed__compbehav__pres_sx
mh_y_ksads__ed__emac__pres_sx
mh_y_ksads__ed__fear__obese__pres_sx
mh_y_ksads__ed__slfwrth__pres_sx
mh_y_ksads__ed__wghtcntrl__oth__pres_sx
mh_y_ksads__ed__wghtcntrl__vom__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 8 items missing
vars_mh_y_ksads__ed__pres__sx compute_mh_y_ksads__ed__pres__sx_mean( data, name = "mh_y_ksads__ed__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ed__pres__sx compute_mh_y_ksads__ed__pres__sx_mean( data, name = "mh_y_ksads__ed__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ed__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ed__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__gad__past__sx_mean
KSADS - Generalized Anxiety Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__gad__worry__6mo__past_sx
mh_y_ksads__gad__worry__diffctrl__past_sx
mh_y_ksads__gad__worry__excess__past_sx
mh_y_ksads__gad__worry__multi__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_y_ksads__gad__past__sx compute_mh_y_ksads__gad__past__sx_mean( data, name = "mh_y_ksads__gad__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__gad__past__sx compute_mh_y_ksads__gad__past__sx_mean( data, name = "mh_y_ksads__gad__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__gad__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__gad__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__gad__pres__sx_mean
KSADS - Generalized Anxiety Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__gad__worry__6mo__pres_sx
mh_y_ksads__gad__worry__diffctrl__pres_sx
mh_y_ksads__gad__worry__excess__pres_sx
mh_y_ksads__gad__worry__multi__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_y_ksads__gad__pres__sx compute_mh_y_ksads__gad__pres__sx_mean( data, name = "mh_y_ksads__gad__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__gad__pres__sx compute_mh_y_ksads__gad__pres__sx_mean( data, name = "mh_y_ksads__gad__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__gad__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__gad__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ocd__past__sx_mean
KSADS - Obsessive Compulsive Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_y_ksads__ocd__compuls__past_sx
mh_y_ksads__ocd__compuls__prvntanx__past_sx
mh_y_ksads__ocd__compuls__tcnsm__past_sx
mh_y_ksads__ocd__obsess__intru__past_sx
mh_y_ksads__ocd__obsess__past_sx
mh_y_ksads__ocd__obsess__tcnsm__past_sx
mh_y_ksads__ocd__suprstho__past_sx
Excluded values:
555
Validation criterion: maximally 1 of 7 items missing
vars_mh_y_ksads__ocd__past__sx compute_mh_y_ksads__ocd__past__sx_mean( data, name = "mh_y_ksads__ocd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ocd__past__sx compute_mh_y_ksads__ocd__past__sx_mean( data, name = "mh_y_ksads__ocd__past__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ocd__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ocd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ocd__pres__sx_mean
KSADS - Obsessive Compulsive Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_y_ksads__ocd__compuls__pres_sx
mh_y_ksads__ocd__compuls__prvntanx__pres_sx
mh_y_ksads__ocd__compuls__tcnsm__pres_sx
mh_y_ksads__ocd__obsess__intru__pres_sx
mh_y_ksads__ocd__obsess__pres_sx
mh_y_ksads__ocd__obsess__tcnsm__pres_sx
mh_y_ksads__ocd__suprstho__pres_sx
Excluded values:
555
Validation criterion: maximally 1 of 7 items missing
vars_mh_y_ksads__ocd__pres__sx compute_mh_y_ksads__ocd__pres__sx_mean( data, name = "mh_y_ksads__ocd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ocd__pres__sx compute_mh_y_ksads__ocd__pres__sx_mean( data, name = "mh_y_ksads__ocd__pres__sx_mean", max_na = 1, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ocd__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ocd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__panic__past__sx_mean
KSADS - Panic Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__panic__attack__maladp__past_sx
mh_y_ksads__panic__attack__past_sx
mh_y_ksads__panic__sympt__past_sx
mh_y_ksads__panic__worry__attack__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_y_ksads__panic__past__sx compute_mh_y_ksads__panic__past__sx_mean( data, name = "mh_y_ksads__panic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__panic__past__sx compute_mh_y_ksads__panic__past__sx_mean( data, name = "mh_y_ksads__panic__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__panic__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__panic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__panic__pres__sx_mean
KSADS - Panic Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__panic__attack__maladp__pres_sx
mh_y_ksads__panic__attack__pres_sx
mh_y_ksads__panic__sympt__pres_sx
mh_y_ksads__panic__worry__attack__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 4 items missing
vars_mh_y_ksads__panic__pres__sx compute_mh_y_ksads__panic__pres__sx_mean( data, name = "mh_y_ksads__panic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__panic__pres__sx compute_mh_y_ksads__panic__pres__sx_mean( data, name = "mh_y_ksads__panic__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__panic__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__panic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ptsd__past__sx_mean
KSADS - Post-Traumatic Stress Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 4 missing or declined]
Summarized variables:
mh_y_ksads__ptsd__anhed__past_sx
mh_y_ksads__ptsd__avoid__extrmnd__past_sx
mh_y_ksads__ptsd__avoid__trmatho__past_sx
mh_y_ksads__ptsd__concprob__past_sx
mh_y_ksads__ptsd__depersnl__past_sx
mh_y_ksads__ptsd__derealztn__past_sx
mh_y_ksads__ptsd__detach__past_sx
mh_y_ksads__ptsd__distortcog__cause__past_sx
mh_y_ksads__ptsd__distortcog__consq__past_sx
mh_y_ksads__ptsd__emot__neg__past_sx
mh_y_ksads__ptsd__emot__nopos__past_sx
mh_y_ksads__ptsd__extrmnd__distrs__past_sx
mh_y_ksads__ptsd__flshbck__past_sx
mh_y_ksads__ptsd__hyprvigl__past_sx
mh_y_ksads__ptsd__intrmnd__distrs__past_sx
mh_y_ksads__ptsd__irrit__past_sx
mh_y_ksads__ptsd__memloss__past_sx
mh_y_ksads__ptsd__negblf__past_sx
mh_y_ksads__ptsd__nghtmr__past_sx
mh_y_ksads__ptsd__physreact__past_sx
mh_y_ksads__ptsd__rckls__past_sx
mh_y_ksads__ptsd__sleepdistb__past_sx
mh_y_ksads__ptsd__startle__past_sx
mh_y_ksads__ptsd__trmatho__intru__past_sx
Excluded values:
555
Validation criterion: maximally 4 of 24 items missing
vars_mh_y_ksads__ptsd__past__sx compute_mh_y_ksads__ptsd__past__sx_mean( data, name = "mh_y_ksads__ptsd__past__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ptsd__past__sx compute_mh_y_ksads__ptsd__past__sx_mean( data, name = "mh_y_ksads__ptsd__past__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ptsd__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ptsd__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__ptsd__pres__sx_mean
KSADS - Post-Traumatic Stress Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 4 missing or declined]
Summarized variables:
mh_y_ksads__ptsd__anhed__pres_sx
mh_y_ksads__ptsd__avoid__extrmnd__pres_sx
mh_y_ksads__ptsd__avoid__trmatho__pres_sx
mh_y_ksads__ptsd__concprob__pres_sx
mh_y_ksads__ptsd__depersnl__pres_sx
mh_y_ksads__ptsd__derealztn__pres_sx
mh_y_ksads__ptsd__detach__pres_sx
mh_y_ksads__ptsd__distortcog__cause__pres_sx
mh_y_ksads__ptsd__distortcog__consq__pres_sx
mh_y_ksads__ptsd__emot__neg__pres_sx
mh_y_ksads__ptsd__emot__nopos__pres_sx
mh_y_ksads__ptsd__extrmnd__distrs__pres_sx
mh_y_ksads__ptsd__flshbck__pres_sx
mh_y_ksads__ptsd__hyprvigl__pres_sx
mh_y_ksads__ptsd__intrmnd__distrs__pres_sx
mh_y_ksads__ptsd__irrit__pres_sx
mh_y_ksads__ptsd__memloss__pres_sx
mh_y_ksads__ptsd__negblf__pres_sx
mh_y_ksads__ptsd__nghtmr__pres_sx
mh_y_ksads__ptsd__physreact__pres_sx
mh_y_ksads__ptsd__rckls__pres_sx
mh_y_ksads__ptsd__sleepdistb__pres_sx
mh_y_ksads__ptsd__startle__pres_sx
mh_y_ksads__ptsd__trmatho__intru__pres_sx
Excluded values:
555
Validation criterion: maximally 4 of 24 items missing
vars_mh_y_ksads__ptsd__pres__sx compute_mh_y_ksads__ptsd__pres__sx_mean( data, name = "mh_y_ksads__ptsd__pres__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__ptsd__pres__sx compute_mh_y_ksads__ptsd__pres__sx_mean( data, name = "mh_y_ksads__ptsd__pres__sx_mean", max_na = 4, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__ptsd__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__ptsd__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__sleep__past__sx_mean
KSADS - Sleep Problems [Youth] (Symptom - Past): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__sleep__insom__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_y_ksads__sleep__past__sx compute_mh_y_ksads__sleep__past__sx_mean( data, name = "mh_y_ksads__sleep__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__sleep__past__sx compute_mh_y_ksads__sleep__past__sx_mean( data, name = "mh_y_ksads__sleep__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__sleep__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__sleep__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__sleep__pres__sx_mean
KSADS - Sleep Problems [Youth] (Symptom - Present): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__sleep__insom__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 1 items missing
vars_mh_y_ksads__sleep__pres__sx compute_mh_y_ksads__sleep__pres__sx_mean( data, name = "mh_y_ksads__sleep__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__sleep__pres__sx compute_mh_y_ksads__sleep__pres__sx_mean( data, name = "mh_y_ksads__sleep__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__sleep__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__sleep__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__socanx__past__sx_mean
KSADS - Social Anxiety Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__socanx__anx__past_sx
mh_y_ksads__socanx__avoid__past_sx
mh_y_ksads__socanx__fear__past_sx
Excluded values:
555
Validation criterion: maximally 0 of 3 items missing
vars_mh_y_ksads__socanx__past__sx compute_mh_y_ksads__socanx__past__sx_mean( data, name = "mh_y_ksads__socanx__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__socanx__past__sx compute_mh_y_ksads__socanx__past__sx_mean( data, name = "mh_y_ksads__socanx__past__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__socanx__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__socanx__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__socanx__pres__sx_mean
KSADS - Social Anxiety Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 0 missing or declined]
Summarized variables:
mh_y_ksads__socanx__anx__pres_sx
mh_y_ksads__socanx__avoid__pres_sx
mh_y_ksads__socanx__fear__pres_sx
Excluded values:
555
Validation criterion: maximally 0 of 3 items missing
vars_mh_y_ksads__socanx__pres__sx compute_mh_y_ksads__socanx__pres__sx_mean( data, name = "mh_y_ksads__socanx__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__socanx__pres__sx compute_mh_y_ksads__socanx__pres__sx_mean( data, name = "mh_y_ksads__socanx__pres__sx_mean", max_na = 0, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__socanx__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__socanx__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__suic__past__sx_mean
KSADS - Suicidality [Youth] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
mh_y_ksads__suic__slfinj__past_sx
mh_y_ksads__suic__slfinj__nointnt__past_sx
mh_y_ksads__suic__slfinj__intnt__past_sx
mh_y_ksads__suic__slfinj__psbldie__past_sx
mh_y_ksads__suic__idea__past_sx
mh_y_ksads__suic__intnt__past_sx
mh_y_ksads__suic__mthd__past_sx
mh_y_ksads__suic__plan__past_sx
mh_y_ksads__suic__prep__past_sx
mh_y_ksads__suic__attmpt__past_sx
mh_y_ksads__suic__attmpt__intrpt__past_sx
mh_y_ksads__suic__attmpt__psbldie__past_sx
mh_y_ksads__suic__wishdead__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 13 items missing
vars_mh_y_ksads__suic__past__sx compute_mh_y_ksads__suic__past__sx_mean( data, name = "mh_y_ksads__suic__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__suic__past__sx compute_mh_y_ksads__suic__past__sx_mean( data, name = "mh_y_ksads__suic__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__suic__past__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__suic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_ksads__suic__pres__sx_mean
KSADS - Suicidality [Youth] (Symptom - Present): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
mh_y_ksads__suic__slfinj__pres_sx
mh_y_ksads__suic__slfinj__nointnt__pres_sx
mh_y_ksads__suic__slfinj__intnt__pres_sx
mh_y_ksads__suic__slfinj__psbldie__pres_sx
mh_y_ksads__suic__idea__pres_sx
mh_y_ksads__suic__intnt__pres_sx
mh_y_ksads__suic__mthd__pres_sx
mh_y_ksads__suic__plan__pres_sx
mh_y_ksads__suic__prep__pres_sx
mh_y_ksads__suic__attmpt__pres_sx
mh_y_ksads__suic__attmpt__intrpt__pres_sx
mh_y_ksads__suic__attmpt__psbldie__pres_sx
mh_y_ksads__suic__wishdead__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 13 items missing
vars_mh_y_ksads__suic__pres__sx compute_mh_y_ksads__suic__pres__sx_mean( data, name = "mh_y_ksads__suic__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_mh_y_ksads__suic__pres__sx compute_mh_y_ksads__suic__pres__sx_mean( data, name = "mh_y_ksads__suic__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_ksads__suic__pres__sx is a character vector
of all column names used to compute summary score of
mh_y_ksads__suic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score mh_y_pai_nm
NIH Toolbox - Positive Affect Items [Youth] (NA): Number missing
Summarized variables:
mh_y_pai_001
mh_y_pai_002
mh_y_pai_003
mh_y_pai_004
mh_y_pai_005
mh_y_pai_006
mh_y_pai_007
mh_y_pai_008
mh_y_pai_009
Excluded values:
777
999
vars_mh_y_pai compute_mh_y_pai_nm( data, name = "mh_y_pai_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_pai compute_mh_y_pai_nm( data, name = "mh_y_pai_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_pai is vector of all column names
used to compute summary score of compute_mh_y_pai scores.
tbl. see combine.
## Not run: compute_mh_y_pai_nm(data) |> select( any_of(c("mh_y_pai_nm", vars_mh_y_pai)) ) ## End(Not run)## Not run: compute_mh_y_pai_nm(data) |> select( any_of(c("mh_y_pai_nm", vars_mh_y_pai)) ) ## End(Not run)
Computes the summary score mh_y_peq__overt__agg_nm
Peer Experiences Questionnaire [Youth] (Overt Aggression): Number
missing
Summarized variables:
mh_y_peq__overt__agg_001
mh_y_peq__overt__agg_002
mh_y_peq__overt__agg_003
Excluded values:
777
vars_mh_y_peq__overt__agg compute_mh_y_peq__overt__agg_nm( data, name = "mh_y_peq__overt__agg_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__overt__agg compute_mh_y_peq__overt__agg_nm( data, name = "mh_y_peq__overt__agg_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__overt__agg is vector of all column names
used to compute summary score of mh_y_peq__overt__agg scores.
tbl. see combine.
## Not run: compute_mh_y_peq__overt__agg_nm(data) |> select( any_of(c("mh_y_peq__overt__agg_nm", vars_mh_y_peq__overt__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__overt__agg_nm(data) |> select( any_of(c("mh_y_peq__overt__agg_nm", vars_mh_y_peq__overt__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__overt__vict_nm
Peer Experiences Questionnaire [Youth] (Overt Victimization): Number
missing
Summarized variables:
mh_y_peq__overt__vict_001
mh_y_peq__overt__vict_002
mh_y_peq__overt__vict_003
Excluded values:
777
vars_mh_y_peq__overt__vict compute_mh_y_peq__overt__vict_nm( data, name = "mh_y_peq__overt__vict_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__overt__vict compute_mh_y_peq__overt__vict_nm( data, name = "mh_y_peq__overt__vict_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__overt__vict is vector of all column names
used to compute summary score of mh_y_peq__overt__vict scores.
tbl. see combine.
## Not run: compute_mh_y_peq__overt__vict_nm(data) |> select( any_of(c("mh_y_peq__overt__vict_nm", vars_mh_y_peq__overt__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__overt__vict_nm(data) |> select( any_of(c("mh_y_peq__overt__vict_nm", vars_mh_y_peq__overt__vict)) ) ## End(Not run)
Computes the summary score mh_y_peq__rel__agg_nm
Peer Experiences Questionnaire [Youth] (Relational Aggression): Number
missing
Summarized variables:
mh_y_peq__rel__agg_001
mh_y_peq__rel__agg_002
mh_y_peq__rel__agg_003
Excluded values:
777
vars_mh_y_peq__rel__agg compute_mh_y_peq__rel__agg_nm( data, name = "mh_y_peq__rel__agg_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__rel__agg compute_mh_y_peq__rel__agg_nm( data, name = "mh_y_peq__rel__agg_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__rel__agg is vector of all column names
used to compute summary score of mh_y_peq__rel__agg scores.
tbl. see combine.
## Not run: compute_mh_y_peq__rel__agg_nm(data) |> select( any_of(c("mh_y_peq__rel__agg_nm", vars_mh_y_peq__rel__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__rel__agg_nm(data) |> select( any_of(c("mh_y_peq__rel__agg_nm", vars_mh_y_peq__rel__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__rel__vict_nm
Peer Experiences Questionnaire [Youth] (Relational Victimization):
Number missing
Summarized variables:
mh_y_peq__rel__vict_001
mh_y_peq__rel__vict_002
mh_y_peq__rel__vict_003
Excluded values:
777
vars_mh_y_peq__rel__vict compute_mh_y_peq__rel__vict_nm( data, name = "mh_y_peq__rel__vict_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__rel__vict compute_mh_y_peq__rel__vict_nm( data, name = "mh_y_peq__rel__vict_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__rel__vict is vector of all column names
used to compute summary score of mh_y_peq__rel__vict scores.
tbl. see combine.
## Not run: compute_mh_y_peq__rel__vict_nm(data) |> select( any_of(c("mh_y_peq__rel__vict_nm", vars_mh_y_peq__rel__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__rel__vict_nm(data) |> select( any_of(c("mh_y_peq__rel__vict_nm", vars_mh_y_peq__rel__vict)) ) ## End(Not run)
Computes the summary score mh_y_peq__rep__agg_nm
Peer Experiences Questionnaire [Youth] (Reputational Aggression):
Number missing
Summarized variables:
mh_y_peq__rep__agg_001
mh_y_peq__rep__agg_002
mh_y_peq__rep__agg_003
Excluded values:
777
vars_mh_y_peq__rep__agg compute_mh_y_peq__rep__agg_nm( data, name = "mh_y_peq__rep__agg_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__rep__agg compute_mh_y_peq__rep__agg_nm( data, name = "mh_y_peq__rep__agg_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__rep__agg is vector of all column names
used to compute summary score of mh_y_peq__rep__agg scores.
tbl. see combine.
## Not run: compute_mh_y_peq__rep__agg_nm(data) |> select( any_of(c("mh_y_peq__rep__agg_nm", vars_mh_y_peq__rep__agg)) ) ## End(Not run)## Not run: compute_mh_y_peq__rep__agg_nm(data) |> select( any_of(c("mh_y_peq__rep__agg_nm", vars_mh_y_peq__rep__agg)) ) ## End(Not run)
Computes the summary score mh_y_peq__rep__vict_nm
Peer Experiences Questionnaire [Youth] (Reputational Victimization):
Number missing
Summarized variables:
mh_y_peq__rep__vict_001
mh_y_peq__rep__vict_002
mh_y_peq__rep__vict_003
Excluded values:
777
vars_mh_y_peq__rep__vict compute_mh_y_peq__rep__vict_nm( data, name = "mh_y_peq__rep__vict_nm", exclude = c("777"), combine = TRUE )vars_mh_y_peq__rep__vict compute_mh_y_peq__rep__vict_nm( data, name = "mh_y_peq__rep__vict_nm", exclude = c("777"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_peq__rep__vict is vector of all column names
used to compute summary score of mh_y_peq__rep__vict scores.
tbl. see combine.
## Not run: compute_mh_y_peq__rep__vict_nm(data) |> select( any_of(c("mh_y_peq__rep__vict_nm", vars_mh_y_peq__rep__vict)) ) ## End(Not run)## Not run: compute_mh_y_peq__rep__vict_nm(data) |> select( any_of(c("mh_y_peq__rep__vict_nm", vars_mh_y_peq__rep__vict)) ) ## End(Not run)
Computes the summary score mh_y_ple_count
Life Events [Youth] (Events): Count
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
Excluded values:
444
777
999
vars_mh_y_ple compute_mh_y_ple_count( data, name = "mh_y_ple_count", combine = TRUE, max_na = NULL )vars_mh_y_ple compute_mh_y_ple_count( data, name = "mh_y_ple_count", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_y_ple is a character vector of all column names
used to compute summary score of mh_y_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_sum
Life Events [Youth] (Severity of Good Events): Sum [Validation: No
more than 5 events missing and no experience/severity items missing or
declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
vars_mh_y_ple__exp compute_mh_y_ple__severity__good_sum( data, name = "mh_y_ple__severity__good_sum", combine = TRUE, max_na = 5 )vars_mh_y_ple__exp compute_mh_y_ple__severity__good_sum( data, name = "mh_y_ple__severity__good_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
vars_mh_y_ple__exp is a character vector of all column names
used to compute summary score of mh_y_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_sum__v01
Life Events [Youth] (Severity of Good Events): Sum - Version 1 (Year
3) [Validation: No more than 6 events missing and no experience/severity
items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
vars_mh_y_ple__exp__v01 compute_mh_y_ple__severity__good_sum__v01( data, name = "mh_y_ple__severity__good_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )vars_mh_y_ple__exp__v01 compute_mh_y_ple__severity__good_sum__v01( data, name = "mh_y_ple__severity__good_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__exp__v01 is a character vector of all column names
used to compute summary score of mh_y_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_sum__v02
Life Events [Youth] (Severity of Good Events): Sum - Version 2
(Year 4 and Year 5) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
vars_mh_y_ple__exp__v02 compute_mh_y_ple__severity__good_sum__v02( data, name = "mh_y_ple__severity__good_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )vars_mh_y_ple__exp__v02 compute_mh_y_ple__severity__good_sum__v02( data, name = "mh_y_ple__severity__good_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__exp__v02 is a character vector of all column names
used to compute summary score of mh_y_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity__good_sum__v03
Life Events [Youth] (Severity of Good Events): Sum - Version 3
(Starting at Year 6) [Validation: No more than 6 events missing and no
experience/severity items missing or declined]
Summarized variables:
mh_y_ple__exp_001
mh_y_ple__exp_002
mh_y_ple__exp_003
mh_y_ple__exp_004
mh_y_ple__exp_005
mh_y_ple__exp_006
mh_y_ple__exp_007
mh_y_ple__exp_008
mh_y_ple__exp_009
mh_y_ple__exp_010
mh_y_ple__exp_011
mh_y_ple__exp_012
mh_y_ple__exp_013
mh_y_ple__exp_014
mh_y_ple__exp_015
mh_y_ple__exp_016
mh_y_ple__exp_017
mh_y_ple__exp_018
mh_y_ple__exp_019
mh_y_ple__exp_020
mh_y_ple__exp_021
mh_y_ple__exp_022
mh_y_ple__exp_023
mh_y_ple__exp_024
mh_y_ple__exp_025
mh_y_ple__exp_026
mh_y_ple__exp_027
mh_y_ple__exp_028
mh_y_ple__exp_029
mh_y_ple__exp_030
mh_y_ple__exp_031
mh_y_ple__exp_032
mh_y_ple__exp_033
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
vars_mh_y_ple__exp__v03 compute_mh_y_ple__severity__good_sum__v03( data, name = "mh_y_ple__severity__good_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )vars_mh_y_ple__exp__v03 compute_mh_y_ple__severity__good_sum__v03( data, name = "mh_y_ple__severity__good_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__exp__v03 is a character vector of all column names
used to compute summary score of mh_y_ple__exp.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_sum
Life Events [Youth] (Severity): Sum [Validation: No more than 5
events missing and no severity items missing or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
Excluded values:
444
777
999
Validation criterion: maximally 5 of 25 items missing
vars_mh_y_ple__severity compute_mh_y_ple__severity_sum( data, name = "mh_y_ple__severity_sum", combine = TRUE, max_na = 5 )vars_mh_y_ple__severity compute_mh_y_ple__severity_sum( data, name = "mh_y_ple__severity_sum", combine = TRUE, max_na = 5 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 5). |
vars_mh_y_ple__severity is a character vector of all column names
used to compute summary score of mh_y_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_sum__v01
Life Events [Youth] (Severity): Sum - Version 1 (Year 3) [Validation:
No more than 6 events missing and no severity items missing or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
Excluded values:
444
777
999
Validation criterion: maximally 6 of 31 items missing
vars_mh_y_ple__severity__v01 compute_mh_y_ple__severity_sum__v01( data, name = "mh_y_ple__severity_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )vars_mh_y_ple__severity__v01 compute_mh_y_ple__severity_sum__v01( data, name = "mh_y_ple__severity_sum__v01", events = "ses-03A", combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__severity__v01 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_sum__v02
Life Events [Youth] (Severity): Sum - Version 2 (Year 4 and Year 5)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 33 items missing
vars_mh_y_ple__severity__v02 compute_mh_y_ple__severity_sum__v02( data, name = "mh_y_ple__severity_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )vars_mh_y_ple__severity__v02 compute_mh_y_ple__severity_sum__v02( data, name = "mh_y_ple__severity_sum__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__severity__v02 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple__severity_sum__v03
Life Events [Youth] (Severity): Sum - Version 3 (Starting at Year 6)
[Validation: No more than 6 events missing and no severity items missing
or declined]
Summarized variables:
mh_y_ple__severity_001
mh_y_ple__severity_002
mh_y_ple__severity_003
mh_y_ple__severity_004
mh_y_ple__severity_005
mh_y_ple__severity_006
mh_y_ple__severity_007
mh_y_ple__severity_008
mh_y_ple__severity_009
mh_y_ple__severity_010
mh_y_ple__severity_011
mh_y_ple__severity_012
mh_y_ple__severity_013
mh_y_ple__severity_014
mh_y_ple__severity_015
mh_y_ple__severity_016
mh_y_ple__severity_017
mh_y_ple__severity_018
mh_y_ple__severity_019
mh_y_ple__severity_020
mh_y_ple__severity_021
mh_y_ple__severity_022
mh_y_ple__severity_023
mh_y_ple__severity_024
mh_y_ple__severity_025
mh_y_ple__severity_026
mh_y_ple__severity_027
mh_y_ple__severity_028
mh_y_ple__severity_029
mh_y_ple__severity_030
mh_y_ple__severity_031
mh_y_ple__severity_032
mh_y_ple__severity_033
mh_y_ple__severity_034
Excluded values:
444
777
999
Validation criterion: maximally 6 of 34 items missing
vars_mh_y_ple__severity__v03 compute_mh_y_ple__severity_sum__v03( data, name = "mh_y_ple__severity_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )vars_mh_y_ple__severity__v03 compute_mh_y_ple__severity_sum__v03( data, name = "mh_y_ple__severity_sum__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = 6 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 6). |
vars_mh_y_ple__severity__v03 is a character vector of all column
names
used to compute summary score of mh_y_ple__severity.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_count__v01
Life Events [Youth] (Events): Count - Version 1 (Year 3)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
Excluded values:
444
777
999
vars_mh_y_ple__v01 compute_mh_y_ple_count__v01( data, name = "mh_y_ple_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )vars_mh_y_ple__v01 compute_mh_y_ple_count__v01( data, name = "mh_y_ple_count__v01", events = "ses-03A", combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_y_ple__v01 is a character vector of all column names
used to compute summary score of mh_y_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_count__v02
Life Events [Youth] (Events): Count - Version 2 (Year 4 and Year 5)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
mh_y_ple_032
mh_y_ple_034
Excluded values:
444
777
999
vars_mh_y_ple__v02 compute_mh_y_ple_count__v02( data, name = "mh_y_ple_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )vars_mh_y_ple__v02 compute_mh_y_ple_count__v02( data, name = "mh_y_ple_count__v02", events = c("ses-04A", "ses-05A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_y_ple__v02 is a character vector of all column names
used to compute summary score of mh_y_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_ple_count__v03
Life Events [Youth] (Events): Count - Version 3 (Starting at Year 6)
Summarized variables:
mh_y_ple_001
mh_y_ple_002
mh_y_ple_003
mh_y_ple_004
mh_y_ple_005
mh_y_ple_006
mh_y_ple_007
mh_y_ple_008
mh_y_ple_009
mh_y_ple_010
mh_y_ple_011
mh_y_ple_012
mh_y_ple_013
mh_y_ple_014
mh_y_ple_015
mh_y_ple_016
mh_y_ple_017
mh_y_ple_018
mh_y_ple_019
mh_y_ple_020
mh_y_ple_021
mh_y_ple_022
mh_y_ple_023
mh_y_ple_024
mh_y_ple_025
mh_y_ple_026
mh_y_ple_027
mh_y_ple_028
mh_y_ple_029
mh_y_ple_030
mh_y_ple_031
mh_y_ple_032
mh_y_ple_033
mh_y_ple_034
Excluded values:
444
777
999
vars_mh_y_ple__v03 compute_mh_y_ple_count__v03( data, name = "mh_y_ple_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )vars_mh_y_ple__v03 compute_mh_y_ple_count__v03( data, name = "mh_y_ple_count__v03", events = c("ses-06A", "ses-07A"), combine = TRUE, max_na = NULL )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
events |
character vector. Event (session ID) to be used. |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_mh_y_ple__v03 is a character vector of all column names
used to compute summary score of mh_y_ple.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score mh_y_pps__bother_nm
Prodromal Psychosis Scale [Youth] (Bother responses): Number missing
Summarized variables:
mh_y_pps__bother_001
mh_y_pps__bother_002
mh_y_pps__bother_003
mh_y_pps__bother_004
mh_y_pps__bother_005
mh_y_pps__bother_006
mh_y_pps__bother_007
mh_y_pps__bother_008
mh_y_pps__bother_009
mh_y_pps__bother_010
mh_y_pps__bother_011
mh_y_pps__bother_012
mh_y_pps__bother_013
mh_y_pps__bother_014
mh_y_pps__bother_015
mh_y_pps__bother_016
mh_y_pps__bother_017
mh_y_pps__bother_018
mh_y_pps__bother_019
mh_y_pps__bother_020
mh_y_pps__bother_021
vars_mh_y_pps__bother compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)vars_mh_y_pps__bother compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_mh_y_pps__bother is a character vector of all
column names used to compute summary of mh_y_pps__bother scores.
The number of missing values in the mh_y_pps__bother score is
calculated by subtracting the number of valid pairs from the total
PPS count for each subject (mh_y_pps_count - bother_pair_good_sum).
A good pair is defined as a pair where the mh_y_pps_count is 1 and
the mh_y_pps__bother is not missing.
## Not run: compute_mh_y_pps__bother_nm(data) |> select( any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother)) ) ## End(Not run)## Not run: compute_mh_y_pps__bother_nm(data) |> select( any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother)) ) ## End(Not run)
Computes the summary score mh_y_pps__severity_nm
Prodromal Psychosis Scale [Youth] (Severity Score): Number missing
Summarized variables:
mh_y_pps__severity_001
mh_y_pps__severity_002
mh_y_pps__severity_003
mh_y_pps__severity_004
mh_y_pps__severity_005
mh_y_pps__severity_006
mh_y_pps__severity_007
mh_y_pps__severity_008
mh_y_pps__severity_009
mh_y_pps__severity_010
mh_y_pps__severity_011
mh_y_pps__severity_012
mh_y_pps__severity_013
mh_y_pps__severity_014
mh_y_pps__severity_015
mh_y_pps__severity_016
mh_y_pps__severity_017
mh_y_pps__severity_018
mh_y_pps__severity_019
mh_y_pps__severity_020
mh_y_pps__severity_021
Excluded values: none
vars_mh_y_pps__severity compute_mh_y_pps__severity_nm( data, name = "mh_y_pps__severity_nm", combine = TRUE )vars_mh_y_pps__severity compute_mh_y_pps__severity_nm( data, name = "mh_y_pps__severity_nm", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_mh_y_pps__severity is a character vector of all column names
used to compute summary of mh_y_pps__severity scores.
The number of missing values in the mh_y_pps__severity score is
calculated by subtracting the number of valid pairs from the total
bother count for each subject
(mh_y_pps__bother_yes_count - severity_pair_good_sum).
A good pair is defined as a pair where the mh_y_pps__bother__yes_count
is 1 and the mh_y_pps__severity is not missing.
compute_mh_y_pps__bother__yes_count()
## Not run: compute_mh_y_pps__severity_nm(data) |> select( any_of(c("mh_y_pps__severity_nm", vars_mh_y_pps__severity)) ) ## End(Not run)## Not run: compute_mh_y_pps__severity_nm(data) |> select( any_of(c("mh_y_pps__severity_nm", vars_mh_y_pps__severity)) ) ## End(Not run)
Computes the summary score mh_y_pps_count
Prodromal Psychosis Scale [Youth] (number of
Summarized variables:
mh_y_pps_001
mh_y_pps_002
mh_y_pps_003
mh_y_pps_004
mh_y_pps_005
mh_y_pps_006
mh_y_pps_007
mh_y_pps_008
mh_y_pps_009
mh_y_pps_010
mh_y_pps_011
mh_y_pps_012
mh_y_pps_013
mh_y_pps_014
mh_y_pps_015
mh_y_pps_016
mh_y_pps_017
mh_y_pps_018
mh_y_pps_019
mh_y_pps_020
mh_y_pps_021
Excluded values: none
Validation criterion: maximally 4 of 21 items missing
vars_mh_y_pps_count compute_mh_y_pps_count( data, name = "mh_y_pps_count", max_na = 4, combine = TRUE )vars_mh_y_pps_count compute_mh_y_pps_count( data, name = "mh_y_pps_count", max_na = 4, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
vars_mh_y_pps_count is a character vector of all column names
used to compute summary score of mh_y_pps_count and mh_y_pps_nm
The mh_y_pps_count is calculated by summing the number of 1s in each
question. If the number of missing values is greater than max_na,
the summary score is set to NA. By default, max_na is set to 4 (20%).
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_mh_y_pps_count(data) |> select( any_of(c("mh_y_pps_count", vars_mh_y_pps_count)) ) ## End(Not run)## Not run: compute_mh_y_pps_count(data) |> select( any_of(c("mh_y_pps_count", vars_mh_y_pps_count)) ) ## End(Not run)
Computes the summary score mh_y_sup_nm
7-Up Mania Inventory [Youth]: Number missing
Summarized variables:
mh_y_sup_001
mh_y_sup_002
mh_y_sup_003
mh_y_sup_004
mh_y_sup_005
mh_y_sup_006
mh_y_sup_007
Excluded values: none
vars_mh_y_sup compute_mh_y_sup_nm(data, name = "mh_y_sup_nm", exclude = NULL, combine = TRUE)vars_mh_y_sup compute_mh_y_sup_nm(data, name = "mh_y_sup_nm", exclude = NULL, combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_sup is vector of all column names
used to compute summary score of mh_y_sup scores.
tbl. see combine.
## Not run: compute_mh_y_sup_nm(data) |> select( any_of(c("mh_y_sup_nm", vars_mh_y_sup)) ) ## End(Not run)## Not run: compute_mh_y_sup_nm(data) |> select( any_of(c("mh_y_sup_nm", vars_mh_y_sup)) ) ## End(Not run)
Computes the summary score mh_y_upps__nurg_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Negative
Urgency): Number missing
Summarized variables:
mh_y_upps__nurg_001
mh_y_upps__nurg_002
mh_y_upps__nurg_003
mh_y_upps__nurg_004
Excluded values: none
vars_mh_y_upps__nurg compute_mh_y_upps__nurg_nm( data, name = "mh_y_upps__nurg_nm", exclude = NULL, combine = TRUE )vars_mh_y_upps__nurg compute_mh_y_upps__nurg_nm( data, name = "mh_y_upps__nurg_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_upps__nurg is vector of all column names
used to compute summary score of mh_y_upps__nurg scores.
tbl. see combine.
## Not run: compute_mh_y_upps__nurg_nm(data) |> select( any_of(c("mh_y_upps__nurg_nm", vars_mh_y_upps__nurg)) ) ## End(Not run)## Not run: compute_mh_y_upps__nurg_nm(data) |> select( any_of(c("mh_y_upps__nurg_nm", vars_mh_y_upps__nurg)) ) ## End(Not run)
Computes the summary score mh_y_upps__pers_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Perseverance (GSSF)): Number missing
Summarized variables:
mh_y_upps__pers_001
mh_y_upps__pers_002
mh_y_upps__pers_003
mh_y_upps__pers_004
Excluded values: none
vars_mh_y_upps__pers compute_mh_y_upps__pers_nm( data, name = "mh_y_upps__pers_nm", exclude = NULL, combine = TRUE )vars_mh_y_upps__pers compute_mh_y_upps__pers_nm( data, name = "mh_y_upps__pers_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_upps__pers is vector of all column names
used to compute summary score of mh_y_upps__pers scores.
tbl. see combine.
## Not run: compute_mh_y_upps__pers_nm(data) |> select( any_of(c("mh_y_upps__pers_nm", vars_mh_y_upps__pers)) ) ## End(Not run)## Not run: compute_mh_y_upps__pers_nm(data) |> select( any_of(c("mh_y_upps__pers_nm", vars_mh_y_upps__pers)) ) ## End(Not run)
Computes the summary score mh_y_upps__plan_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Lack of
Planning): Number missing
Summarized variables:
mh_y_upps__plan_001
mh_y_upps__plan_002
mh_y_upps__plan_003
mh_y_upps__plan_004
Excluded values: none
vars_mh_y_upps__plan compute_mh_y_upps__plan_nm( data, name = "mh_y_upps__plan_nm", exclude = NULL, combine = TRUE )vars_mh_y_upps__plan compute_mh_y_upps__plan_nm( data, name = "mh_y_upps__plan_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_upps__plan is vector of all column names
used to compute summary score of mh_y_upps__plan scores.
tbl. see combine.
## Not run: compute_mh_y_upps__plan_nm(data) |> select( any_of(c("mh_y_upps__plan_nm", vars_mh_y_upps__plan)) ) ## End(Not run)## Not run: compute_mh_y_upps__plan_nm(data) |> select( any_of(c("mh_y_upps__plan_nm", vars_mh_y_upps__plan)) ) ## End(Not run)
Computes the summary score mh_y_upps__purg_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Positive
Urgency): Number missing
Summarized variables:
mh_y_upps__purg_001
mh_y_upps__purg_002
mh_y_upps__purg_003
mh_y_upps__purg_004
Excluded values: none
vars_mh_y_upps__purg compute_mh_y_upps__purg_nm( data, name = "mh_y_upps__purg_nm", exclude = NULL, combine = TRUE )vars_mh_y_upps__purg compute_mh_y_upps__purg_nm( data, name = "mh_y_upps__purg_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_upps__purg is vector of all column names
used to compute summary score of mh_y_upps__purg scores.
tbl. see combine.
## Not run: compute_mh_y_upps__purg_nm(data) |> select( any_of(c("mh_y_upps__purg_nm", vars_mh_y_upps__purg)) ) ## End(Not run)## Not run: compute_mh_y_upps__purg_nm(data) |> select( any_of(c("mh_y_upps__purg_nm", vars_mh_y_upps__purg)) ) ## End(Not run)
Computes the summary score mh_y_upps__sens_nm
Urgency, Premeditation, Perseverance, Sensation Seeking, Positive
Urgency, Impulsive Behavior Scale (Short Version) [Youth] (Sensation
Seeking): Number missing
Summarized variables:
mh_y_upps__sens_001
mh_y_upps__sens_002
mh_y_upps__sens_003
mh_y_upps__sens_004
Excluded values: none
vars_mh_y_upps__sens compute_mh_y_upps__sens_nm( data, name = "mh_y_upps__sens_nm", exclude = NULL, combine = TRUE )vars_mh_y_upps__sens compute_mh_y_upps__sens_nm( data, name = "mh_y_upps__sens_nm", exclude = NULL, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_mh_y_upps__sens is vector of all column names
used to compute summary score of mh_y_upps__sens scores.
tbl. see combine.
## Not run: compute_mh_y_upps__sens_nm(data) |> select( any_of(c("mh_y_upps__sens_nm", vars_mh_y_upps__sens)) ) ## End(Not run)## Not run: compute_mh_y_upps__sens_nm(data) |> select( any_of(c("mh_y_upps__sens_nm", vars_mh_y_upps__sens)) ) ## End(Not run)
Computes the summary score mh_y_ysr_nm
Youth Self Report [Youth]: Number missing
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr_003
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__attn_001
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn_004
mh_y_ysr__rule_001
mh_y_ysr__rule_002
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule_005
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep_005
mh_y_ysr__som_001
mh_y_ysr__othpr_001
mh_y_ysr__othpr_002
mh_y_ysr__othpr_003
mh_y_ysr__othpr_004
mh_y_ysr__othpr_005
mh_y_ysr__othpr_006
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
Excluded values:
777
999
vars_mh_y_ysr compute_mh_y_ysr_nm( data, name = "mh_y_ysr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr compute_mh_y_ysr_nm( data, name = "mh_y_ysr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr is vector of all column names
used to compute summary score of mh_y_ysr scores.
tbl. see combine.
## Not run: compute_mh_y_ysr_nm(data) |> select( any_of(c("mh_y_ysr_nm", vars_mh_y_ysr)) ) ## End(Not run)## Not run: compute_mh_y_ysr_nm(data) |> select( any_of(c("mh_y_ysr_nm", vars_mh_y_ysr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__adhd_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - ADHD): Number
missing
Summarized variables:
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn__adhd_005
mh_y_ysr__othpr__adhd_001
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
vars_mh_y_ysr__dsm__adhd compute_mh_y_ysr__dsm__adhd_nm( data, name = "mh_y_ysr__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__adhd compute_mh_y_ysr__dsm__adhd_nm( data, name = "mh_y_ysr__dsm__adhd_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__adhd is vector of all column names
used to compute summary score of mh_y_ysr__dsm__adhd scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__adhd_nm(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_nm", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__adhd_nm(data) |> select( any_of(c("mh_y_ysr__dsm__adhd_nm", vars_mh_y_ysr__dsm__adhd)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__anx_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Anxiety problems):
Number missing
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep__anx_004
mh_y_ysr__som__anx_001
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
vars_mh_y_ysr__dsm__anx compute_mh_y_ysr__dsm__anx_nm( data, name = "mh_y_ysr__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__anx compute_mh_y_ysr__dsm__anx_nm( data, name = "mh_y_ysr__dsm__anx_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__anx is vector of all column names
used to compute summary score of mh_y_ysr__dsm__anx scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__anx_nm(data) |> select( any_of(c("mh_y_ysr__dsm__anx_nm", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__anx_nm(data) |> select( any_of(c("mh_y_ysr__dsm__anx_nm", vars_mh_y_ysr__dsm__anx)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__cond_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Conduct problems):
Number missing
Summarized variables:
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr__cond_002
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__aggr__cond_003
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__aggr__cond_004
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__aggr__cond_005
mh_y_ysr__rule__cond_010
Excluded values:
777
999
vars_mh_y_ysr__dsm__cond compute_mh_y_ysr__dsm__cond_nm( data, name = "mh_y_ysr__dsm__cond_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__cond compute_mh_y_ysr__dsm__cond_nm( data, name = "mh_y_ysr__dsm__cond_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__cond is vector of all column names
used to compute summary score of mh_y_ysr__dsm__cond scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__cond_nm(data) |> select( any_of(c("mh_y_ysr__dsm__cond_nm", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__cond_nm(data) |> select( any_of(c("mh_y_ysr__dsm__cond_nm", vars_mh_y_ysr__dsm__cond)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__dep_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Depressive
problems): Number missing
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__anxdep__dep_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__dep_003
mh_y_ysr__som__dep_001
mh_y_ysr__tho__dep_002
mh_y_ysr__othpr__dep_002
mh_y_ysr__tho__dep_003
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
Excluded values:
777
999
vars_mh_y_ysr__dsm__dep compute_mh_y_ysr__dsm__dep_nm( data, name = "mh_y_ysr__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__dep compute_mh_y_ysr__dsm__dep_nm( data, name = "mh_y_ysr__dsm__dep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__dep is vector of all column names
used to compute summary score of mh_y_ysr__dsm__dep scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__dep_nm(data) |> select( any_of(c("mh_y_ysr__dsm__dep_nm", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__dep_nm(data) |> select( any_of(c("mh_y_ysr__dsm__dep_nm", vars_mh_y_ysr__dsm__dep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__opp_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Oppositional Defiant
problems): Number missing
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr__opp_005
Excluded values:
777
999
vars_mh_y_ysr__dsm__opp compute_mh_y_ysr__dsm__opp_nm( data, name = "mh_y_ysr__dsm__opp_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__opp compute_mh_y_ysr__dsm__opp_nm( data, name = "mh_y_ysr__dsm__opp_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__opp is vector of all column names
used to compute summary score of mh_y_ysr__dsm__opp scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__opp_nm(data) |> select( any_of(c("mh_y_ysr__dsm__opp_nm", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__opp_nm(data) |> select( any_of(c("mh_y_ysr__dsm__opp_nm", vars_mh_y_ysr__dsm__opp)) ) ## End(Not run)
Computes the summary score mh_y_ysr__dsm__somat_nm
Youth Self Report [Youth] (DSM-5 Oriented Scale - Somatic complaints):
Number missing
Summarized variables:
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
vars_mh_y_ysr__dsm__somat compute_mh_y_ysr__dsm__somat_nm( data, name = "mh_y_ysr__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__dsm__somat compute_mh_y_ysr__dsm__somat_nm( data, name = "mh_y_ysr__dsm__somat_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__dsm__somat is vector of all column names
used to compute summary score of mh_y_ysr__dsm__somat scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__dsm__somat_nm(data) |> select( any_of(c("mh_y_ysr__dsm__somat_nm", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)## Not run: compute_mh_y_ysr__dsm__somat_nm(data) |> select( any_of(c("mh_y_ysr__dsm__somat_nm", vars_mh_y_ysr__dsm__somat)) ) ## End(Not run)
Computes the summary score mh_y_ysr__pos_nm
Youth Self Report [Youth] (Positive): Number missing
Summarized variables:
mh_y_ysr__pos_001
mh_y_ysr__pos_002
mh_y_ysr__pos_003
mh_y_ysr__pos_004
mh_y_ysr__pos_005
mh_y_ysr__pos_006
mh_y_ysr__pos_007
mh_y_ysr__pos_008
mh_y_ysr__pos_009
mh_y_ysr__pos_010
mh_y_ysr__pos_011
mh_y_ysr__pos_012
mh_y_ysr__pos_013
mh_y_ysr__pos_014
Excluded values:
777
999
vars_mh_y_ysr__pos compute_mh_y_ysr__pos_nm( data, name = "mh_y_ysr__pos_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__pos compute_mh_y_ysr__pos_nm( data, name = "mh_y_ysr__pos_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__pos is vector of all column names
used to compute summary score of mh_y_ysr__pos scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__pos_nm(data) |> select( any_of(c("mh_y_ysr__pos_nm", vars_mh_y_ysr__pos)) ) ## End(Not run)## Not run: compute_mh_y_ysr__pos_nm(data) |> select( any_of(c("mh_y_ysr__pos_nm", vars_mh_y_ysr__pos)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__aggr_nm
Youth Self Report [Youth] (Syndrome Scale - Aggressive behavior):
Number missing
Summarized variables:
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
vars_mh_y_ysr__synd__aggr compute_mh_y_ysr__synd__aggr_nm( data, name = "mh_y_ysr__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__aggr compute_mh_y_ysr__synd__aggr_nm( data, name = "mh_y_ysr__synd__aggr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__aggr is vector of all column names
used to compute summary score of mh_y_ysr__synd__aggr scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__aggr_nm(data) |> select( any_of(c("mh_y_ysr__synd__aggr_nm", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__aggr_nm(data) |> select( any_of(c("mh_y_ysr__synd__aggr_nm", vars_mh_y_ysr__synd__aggr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__anxdep_nm
Youth Self Report [Youth] (Syndrome Scale - Anxious/Depressed): Number
missing
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
Excluded values:
777
999
vars_mh_y_ysr__synd__anxdep compute_mh_y_ysr__synd__anxdep_nm( data, name = "mh_y_ysr__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__anxdep compute_mh_y_ysr__synd__anxdep_nm( data, name = "mh_y_ysr__synd__anxdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__anxdep is vector of all column names
used to compute summary score of mh_y_ysr__synd__anxdep scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__anxdep_nm(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_nm", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__anxdep_nm(data) |> select( any_of(c("mh_y_ysr__synd__anxdep_nm", vars_mh_y_ysr__synd__anxdep)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__attn_nm
Youth Self Report [Youth] (Syndrome Scale - Attention problems):
Number missing
Summarized variables:
mh_y_ysr__attn_001
mh_y_ysr__attn__adhd_001
mh_y_ysr__attn__adhd_002
mh_y_ysr__attn__adhd_003
mh_y_ysr__attn_002
mh_y_ysr__attn_003
mh_y_ysr__attn__adhd_004
mh_y_ysr__attn_004
mh_y_ysr__attn__adhd_005
Excluded values:
777
999
vars_mh_y_ysr__synd__attn compute_mh_y_ysr__synd__attn_nm( data, name = "mh_y_ysr__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__attn compute_mh_y_ysr__synd__attn_nm( data, name = "mh_y_ysr__synd__attn_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__attn is vector of all column names
used to compute summary score of mh_y_ysr__synd__attn scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__attn_nm(data) |> select( any_of(c("mh_y_ysr__synd__attn_nm", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__attn_nm(data) |> select( any_of(c("mh_y_ysr__synd__attn_nm", vars_mh_y_ysr__synd__attn)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__ext_nm
Youth Self Report [Youth] (Syndrome Scale - External): Number missing
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
mh_y_ysr__aggr__opp_001
mh_y_ysr__aggr__cond_001
mh_y_ysr__aggr_001
mh_y_ysr__aggr_002
mh_y_ysr__aggr__cond_002
mh_y_ysr__aggr__opp_002
mh_y_ysr__aggr__opp_003
mh_y_ysr__aggr__cond_003
mh_y_ysr__aggr__cond_004
mh_y_ysr__aggr_003
mh_y_ysr__aggr__opp_004
mh_y_ysr__aggr_004
mh_y_ysr__aggr_005
mh_y_ysr__aggr_006
mh_y_ysr__aggr__opp_005
mh_y_ysr__aggr__cond_005
mh_y_ysr__aggr__adhd_001
Excluded values:
777
999
vars_mh_y_ysr__synd__ext compute_mh_y_ysr__synd__ext_nm( data, name = "mh_y_ysr__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__ext compute_mh_y_ysr__synd__ext_nm( data, name = "mh_y_ysr__synd__ext_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__ext is vector of all column names
used to compute summary score of mh_y_ysr__synd__ext scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__ext_nm(data) |> select( any_of(c("mh_y_ysr__synd__ext_nm", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__ext_nm(data) |> select( any_of(c("mh_y_ysr__synd__ext_nm", vars_mh_y_ysr__synd__ext)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__int_nm
Youth Self Report [Youth] (Syndrome Scale - Internaling): Number
missing
Summarized variables:
mh_y_ysr__anxdep__dep_001
mh_y_ysr__anxdep__anx_001
mh_y_ysr__anxdep__anx_002
mh_y_ysr__anxdep__anx_003
mh_y_ysr__anxdep_001
mh_y_ysr__anxdep_002
mh_y_ysr__anxdep__dep_002
mh_y_ysr__anxdep__anx_004
mh_y_ysr__anxdep__anx_005
mh_y_ysr__anxdep__dep_003
mh_y_ysr__anxdep__anx_006
mh_y_ysr__anxdep__anx_007
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
vars_mh_y_ysr__synd__int compute_mh_y_ysr__synd__int_nm( data, name = "mh_y_ysr__synd__int_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__int compute_mh_y_ysr__synd__int_nm( data, name = "mh_y_ysr__synd__int_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__int is vector of all column names
used to compute summary score of mh_y_ysr__synd__int scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__int_nm(data) |> select( any_of(c("mh_y_ysr__synd__int_nm", vars_mh_y_ysr__synd__int)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__int_nm(data) |> select( any_of(c("mh_y_ysr__synd__int_nm", vars_mh_y_ysr__synd__int)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__othpr_nm
Youth Self Report [Youth] (Other problems): Number missing
Summarized variables:
mh_y_ysr__othpr_001
mh_y_ysr__othpr__dep_001
mh_y_ysr__othpr_002
mh_y_ysr__othpr_003
mh_y_ysr__othpr_004
mh_y_ysr__othpr_005
mh_y_ysr__othpr_006
mh_y_ysr__othpr__dep_002
mh_y_ysr__othpr__adhd_001
Excluded values:
777
999
vars_mh_y_ysr__synd__othpr compute_mh_y_ysr__synd__othpr_nm( data, name = "mh_y_ysr__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__othpr compute_mh_y_ysr__synd__othpr_nm( data, name = "mh_y_ysr__synd__othpr_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__othpr is vector of all column names
used to compute summary score of mh_y_ysr__synd__othpr scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__othpr_nm(data) |> select( any_of(c("mh_y_ysr__synd__othpr_nm", vars_mh_y_ysr__synd__othpr)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__othpr_nm(data) |> select( any_of(c("mh_y_ysr__synd__othpr_nm", vars_mh_y_ysr__synd__othpr)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__rule_nm
Youth Self Report [Youth] (Syndrome Scale - Rule breaking behavior):
Number missing
Summarized variables:
mh_y_ysr__rule_001
mh_y_ysr__rule__cond_001
mh_y_ysr__rule__cond_002
mh_y_ysr__rule__cond_003
mh_y_ysr__rule__cond_004
mh_y_ysr__rule_002
mh_y_ysr__rule__cond_005
mh_y_ysr__rule__cond_006
mh_y_ysr__rule__cond_007
mh_y_ysr__rule__cond_008
mh_y_ysr__rule__cond_009
mh_y_ysr__rule_003
mh_y_ysr__rule_004
mh_y_ysr__rule__cond_010
mh_y_ysr__rule_005
Excluded values:
777
999
vars_mh_y_ysr__synd__rule compute_mh_y_ysr__synd__rule_nm( data, name = "mh_y_ysr__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__rule compute_mh_y_ysr__synd__rule_nm( data, name = "mh_y_ysr__synd__rule_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__rule is vector of all column names
used to compute summary score of mh_y_ysr__synd__rule scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__rule_nm(data) |> select( any_of(c("mh_y_ysr__synd__rule_nm", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__rule_nm(data) |> select( any_of(c("mh_y_ysr__synd__rule_nm", vars_mh_y_ysr__synd__rule)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__soc_nm
Youth Self Report [Youth] (Syndrome Scale -Social problems): Number
missing
Summarized variables:
mh_y_ysr__soc__anx_001
mh_y_ysr__soc_001
mh_y_ysr__soc_002
mh_y_ysr__soc_003
mh_y_ysr__soc_004
mh_y_ysr__soc_005
mh_y_ysr__soc_006
mh_y_ysr__soc_007
mh_y_ysr__soc_008
mh_y_ysr__soc_009
mh_y_ysr__soc_010
Excluded values:
777
999
vars_mh_y_ysr__synd__soc compute_mh_y_ysr__synd__soc_nm( data, name = "mh_y_ysr__synd__soc_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__soc compute_mh_y_ysr__synd__soc_nm( data, name = "mh_y_ysr__synd__soc_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__soc is vector of all column names
used to compute summary score of mh_y_ysr__synd__soc scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__soc_nm(data) |> select( any_of(c("mh_y_ysr__synd__soc_nm", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__soc_nm(data) |> select( any_of(c("mh_y_ysr__synd__soc_nm", vars_mh_y_ysr__synd__soc)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__som_nm
Youth Self Report [Youth] (Syndrome Scale - Somatic complaints):
Number missing
Summarized variables:
mh_y_ysr__som__anx_001
mh_y_ysr__som_001
mh_y_ysr__som__dep_001
mh_y_ysr__som__somat_001
mh_y_ysr__som__somat_002
mh_y_ysr__som__somat_003
mh_y_ysr__som__somat_004
mh_y_ysr__som__somat_005
mh_y_ysr__som__somat_006
mh_y_ysr__som__somat_007
Excluded values:
777
999
vars_mh_y_ysr__synd__som compute_mh_y_ysr__synd__som_nm( data, name = "mh_y_ysr__synd__som_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__som compute_mh_y_ysr__synd__som_nm( data, name = "mh_y_ysr__synd__som_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__som is vector of all column names
used to compute summary score of mh_y_ysr__synd__som scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__som_nm(data) |> select( any_of(c("mh_y_ysr__synd__som_nm", vars_mh_y_ysr__synd__som)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__som_nm(data) |> select( any_of(c("mh_y_ysr__synd__som_nm", vars_mh_y_ysr__synd__som)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__tho_nm
Youth Self Report [Youth] (Syndrome Scale - Thought problems): Number
missing
Summarized variables:
mh_y_ysr__tho_001
mh_y_ysr__tho_002
mh_y_ysr__tho_003
mh_y_ysr__tho_004
mh_y_ysr__tho_005
mh_y_ysr__tho_006
mh_y_ysr__tho__dep_002
mh_y_ysr__tho_007
mh_y_ysr__tho_008
mh_y_ysr__tho_009
mh_y_ysr__tho__dep_003
Excluded values:
777
999
vars_mh_y_ysr__synd__tho compute_mh_y_ysr__synd__tho_nm( data, name = "mh_y_ysr__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__tho compute_mh_y_ysr__synd__tho_nm( data, name = "mh_y_ysr__synd__tho_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__tho is vector of all column names
used to compute summary score of mh_y_ysr__synd__tho scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__tho_nm(data) |> select( any_of(c("mh_y_ysr__synd__tho_nm", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__tho_nm(data) |> select( any_of(c("mh_y_ysr__synd__tho_nm", vars_mh_y_ysr__synd__tho)) ) ## End(Not run)
Computes the summary score mh_y_ysr__synd__wthdep_nm
Youth Self Report [Youth] (Syndrome Scale - Withdrawn/Depressed):
Number missing
Summarized variables:
mh_y_ysr__wthdep__dep_001
mh_y_ysr__wthdep_001
mh_y_ysr__wthdep_002
mh_y_ysr__wthdep_003
mh_y_ysr__wthdep_004
mh_y_ysr__wthdep__dep_002
mh_y_ysr__wthdep__dep_003
mh_y_ysr__wthdep_005
Excluded values:
777
999
vars_mh_y_ysr__synd__wthdep compute_mh_y_ysr__synd__wthdep_nm( data, name = "mh_y_ysr__synd__wthdep_nm", exclude = c("777", "999"), combine = TRUE )vars_mh_y_ysr__synd__wthdep compute_mh_y_ysr__synd__wthdep_nm( data, name = "mh_y_ysr__synd__wthdep_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score. |
combine |
logical. If |
vars_mh_y_ysr__synd__wthdep is vector of all column names
used to compute summary score of mh_y_ysr__synd__wthdep scores.
tbl. see combine.
## Not run: compute_mh_y_ysr__synd__wthdep_nm(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_nm", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)## Not run: compute_mh_y_ysr__synd__wthdep_nm(data) |> select( any_of(c("mh_y_ysr__synd__wthdep_nm", vars_mh_y_ysr__synd__wthdep)) ) ## End(Not run)
Computes the summary score nc_p_bdefs_sum
Barkley Deficits in Executive Functioning Scale [Parent] (EF Summary
Score): Sum
Summarized variables:
nc_p_bdefs_001
nc_p_bdefs_002
nc_p_bdefs_003
nc_p_bdefs_004
nc_p_bdefs_005
nc_p_bdefs_006
nc_p_bdefs_007
nc_p_bdefs_008
nc_p_bdefs_009
nc_p_bdefs_010
nc_p_bdefs_011
nc_p_bdefs_012
nc_p_bdefs_013
nc_p_bdefs_014
nc_p_bdefs_015
nc_p_bdefs_016
nc_p_bdefs_017
nc_p_bdefs_018
nc_p_bdefs_019
nc_p_bdefs_020
vars_nc_p_bdefs compute_nc_p_bdefs_sum( data, name = "nc_p_bdefs_sum", max_na = 0, combine = TRUE )vars_nc_p_bdefs compute_nc_p_bdefs_sum( data, name = "nc_p_bdefs_sum", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
vars_nc_p_bdefs is a character vector of all column names
used to compute summary scores of nc_p_bdefs.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_nc_p_bdefs_sum(data) |> select( data, all_of(c("nc_p_bdefs_sum", vars_nc_p_bdefs)) ) ## End(Not run)## Not run: compute_nc_p_bdefs_sum(data) |> select( data, all_of(c("nc_p_bdefs_sum", vars_nc_p_bdefs)) ) ## End(Not run)
Computes the summary score nc_y_ehis_score
Edinburgh Handedness Inventory [Youth] (Handedness score rating)
Summarized variables:
nc_y_ehis_001
nc_y_ehis_002
nc_y_ehis_003
nc_y_ehis_004
vars_nc_y_ehis compute_nc_y_ehis_score( data, name = "nc_y_ehis_score", max_na = 0, combine = TRUE )vars_nc_y_ehis compute_nc_y_ehis_score( data, name = "nc_y_ehis_score", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
combine |
logical, If |
vars_nc_y_ehis is a character vector of all column names
used to compute summary scores of nc_y_ehis.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_nc_y_ehis_score(data) |> select( data, all_of(c("nc_y_ehis_score", vars_nc_y_ehis)) ) ## End(Not run)## Not run: compute_nc_y_ehis_score(data) |> select( data, all_of(c("nc_y_ehis_score", vars_nc_y_ehis)) ) ## End(Not run)
Computes the summary score nt_p_yst__pmum_mean
Youth Screen Time [Parent] (Problematic Media Use): Mean [Validation:
No more than 1 missing or declined]
Summarized variables:
nt_p_yst__pmum_001
nt_p_yst__pmum_002
nt_p_yst__pmum_003
nt_p_yst__pmum_004
nt_p_yst__pmum_005
nt_p_yst__pmum_006
nt_p_yst__pmum_007
nt_p_yst__pmum_008
nt_p_yst__pmum_009
Excluded values:
777
999
vars_nt_p_yst__pmum compute_nt_p_yst__pmum_mean( data, name = "nt_p_yst__pmum_mean", max_na = 1, combine = TRUE )vars_nt_p_yst__pmum compute_nt_p_yst__pmum_mean( data, name = "nt_p_yst__pmum_mean", max_na = 1, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_nt_p_yst__pmum is a character vector of all column names
used to compute summary score of nt_p_yst__pmum_mean.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_p_yst__screen__wkdy_sum
Youth Screen Time [Parent] (Weekday): Sum
Summarized variables:
nt_p_yst__wkdy__hr_001
nt_p_yst__wkdy__min_001
nt_p_yst__wkdy__min_001__v01
Excluded values:
777
999
Validation criterion: maximally 0 of 1 item missing
vars_nt_p_yst__screen__wkdy compute_nt_p_yst__screen__wkdy_sum( data, name = "nt_p_yst__screen__wkdy_sum", max_na = 0, combine = TRUE )vars_nt_p_yst__screen__wkdy compute_nt_p_yst__screen__wkdy_sum( data, name = "nt_p_yst__screen__wkdy_sum", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_nt_p_yst__screen__wkdy is a character vector of all column names
used to compute summary score of nt_p_yst__screen__wkdy.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_p_yst__screen__wknd_sum
Youth Screen Time [Parent] (Weekend): Sum
Summarized variables:
nt_p_yst__wknd__hr_001
nt_p_yst__wknd__min_001
nt_p_yst__wknd__min_001__v01
Excluded values:
777
999
Validation criterion: maximally 0 of 1 item missing
vars_nt_p_yst__screen__wknd compute_nt_p_yst__screen__wknd_sum( data, name = "nt_p_yst__screen__wknd_sum", max_na = 0, combine = TRUE )vars_nt_p_yst__screen__wknd compute_nt_p_yst__screen__wknd_sum( data, name = "nt_p_yst__screen__wknd_sum", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_nt_p_yst__screen__wknd is a character vector of all column names
used to compute summary score of nt_p_yst__screen__wknd.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_y_stq__screen__wkdy_sum
Screen Time [Youth] (Weekday): Sum
Summarized variables:
nt_y_stq__screen__wkdy_001
nt_y_stq__screen__wkdy_002
nt_y_stq__screen__wkdy_003
nt_y_stq__screen__wkdy_004
nt_y_stq__screen__wkdy_005
nt_y_stq__screen__wkdy_006
nt_y_stq__screen__wkdy__hr_001
nt_y_stq__screen__wkdy__min_001
nt_y_stq__screen__wkdy__hr_001__v01
nt_y_stq__screen__wkdy__min_001__v01
nt_y_stq__screen__wkdy__hr_002
nt_y_stq__screen__wkdy__min_002
nt_y_stq__screen__wkdy__hr_003
nt_y_stq__screen__wkdy__min_003
nt_y_stq__screen__wkdy__hr_004
nt_y_stq__screen__wkdy__min_004
nt_y_stq__screen__wkdy__hr_005
nt_y_stq__screen__wkdy__min_005
nt_y_stq__screen__wkdy__hr_006
nt_y_stq__screen__wkdy__min_006
nt_y_stq__screen__wkdy__hr_007
nt_y_stq__screen__wkdy__min_007
nt_y_stq__screen__wkdy__hr_008
nt_y_stq__screen__wkdy__min_008
nt_y_stq__screen__wkdy__hr_009
nt_y_stq__screen__wkdy__min_009
Excluded values:
777
999
Validation criterion: none missing
vars_nt_y_stq__screen__wkdy compute_nt_y_stq__screen__wkdy_sum( data, name = "nt_y_stq__screen__wkdy_sum", max_na = 0, combine = TRUE )vars_nt_y_stq__screen__wkdy compute_nt_y_stq__screen__wkdy_sum( data, name = "nt_y_stq__screen__wkdy_sum", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_nt_y_stq__screen__wkdy is a character vector of all column names
used to compute summary score of nt_y_stq__screen__wkdy.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score nt_y_stq__screen__wknd_sum
Screen Time [Youth] (Weekend): Sum
Summarized variables:
nt_y_stq__screen__wknd_001
nt_y_stq__screen__wknd_002
nt_y_stq__screen__wknd_003
nt_y_stq__screen__wknd_004
nt_y_stq__screen__wknd_005
nt_y_stq__screen__wknd_006
nt_y_stq__screen__wknd__hr_001
nt_y_stq__screen__wknd__min_001
nt_y_stq__screen__wknd__hr_001__v01
nt_y_stq__screen__wknd__min_001__v01
nt_y_stq__screen__wknd__hr_002
nt_y_stq__screen__wknd__min_002
nt_y_stq__screen__wknd__hr_003
nt_y_stq__screen__wknd__min_003
nt_y_stq__screen__wknd__hr_004
nt_y_stq__screen__wknd__min_004
nt_y_stq__screen__wknd__hr_005
nt_y_stq__screen__wknd__min_005
nt_y_stq__screen__wknd__hr_006
nt_y_stq__screen__wknd__min_006
nt_y_stq__screen__wknd__hr_007
nt_y_stq__screen__wknd__min_007
nt_y_stq__screen__wknd__hr_008
nt_y_stq__screen__wknd__min_008
nt_y_stq__screen__wknd__hr_009
nt_y_stq__screen__wknd__min_009
Excluded values:
777
999
Validation criterion: none missing
vars_nt_y_stq__screen__wknd compute_nt_y_stq__screen__wknd_sum( data, name = "nt_y_stq__screen__wknd_sum", max_na = 0, combine = TRUE )vars_nt_y_stq__screen__wknd compute_nt_y_stq__screen__wknd_sum( data, name = "nt_y_stq__screen__wknd_sum", max_na = 0, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_nt_y_stq__screen__wknd is a character vector of all column names
used to compute summary score of nt_y_stq__screen__wknd.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_anthr__fath_height__in
Anthropometrics [Parent] (Height): Father's height (in)
Summarized variables:
ph_p_anthr__height__fath_001
ph_p_anthr__height__fath_001__01
Excluded values: None
Validation criterion: None
vars_ph_p_anthr__height compute_ph_p_anthr__fath_height__in( data, name = "ph_p_anthr__fath_height__in", combine = TRUE )vars_ph_p_anthr__height compute_ph_p_anthr__fath_height__in( data, name = "ph_p_anthr__fath_height__in", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_anthr__fath_height__in and
ph_p_anthr__moth_height__in.
## Not run: compute_ph_p_anthr__fath_height__in(data) |> select( all_of(c("ph_p_anthr__fath_height__in", vars_ph_p_anthr__height)) ) ## End(Not run)## Not run: compute_ph_p_anthr__fath_height__in(data) |> select( all_of(c("ph_p_anthr__fath_height__in", vars_ph_p_anthr__height)) ) ## End(Not run)
Computes the summary score ph_p_cna_sum
Child Nutrition Assessment [Parent]: Sum [Validation: No more than 0
missing or declined]
Summarized variables:
ph_p_cna_001
ph_p_cna_002
ph_p_cna_003
ph_p_cna_004
ph_p_cna_005
ph_p_cna_006
ph_p_cna_007
ph_p_cna_008
ph_p_cna_009
ph_p_cna_010
ph_p_cna_011
ph_p_cna_012
ph_p_cna_013
ph_p_cna_014
Excluded values:
999
777
Validation criterion: maximally 0 of 14 items missing
vars_ph_p_cna compute_ph_p_cna_sum( data, name = "ph_p_cna_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_cna compute_ph_p_cna_sum( data, name = "ph_p_cna_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
vars_ph_p_cna is a character vector of all column names
used to compute summary scores of ph_p_cna.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_p_cna_sum(data) |> select( all_of(c("ph_p_cna_sum", vars_ph_p_cna)) ) ## End(Not run)## Not run: compute_ph_p_cna_sum(data) |> select( all_of(c("ph_p_cna_sum", vars_ph_p_cna)) ) ## End(Not run)
Computes the summary score ph_p_dhx_birthweight
Developmental History [Parent]: Youth birth weight
Summarized variables:
ph_p_dhx_002__01
ph_p_dhx_002__02
Excluded values:
999
any value less than 0
Notes:
Computed using only baseline (ses-00A) and four-year (ses-04A) data
The following transformations were made prior to computing the score:
if ph_p_dhx_002__01 < 2, set it to 2
if ph_p_dhx_002__01 > 15, set it to 15
if ph_p_dhx_002__02 > 15 / 16, set it to 15 / 16
The following decisions were made based on discordance between baseline and four-year data:
if discordance is <= 1, take baseline weight
if discordance is > 1 and baseline weight is > 4, take baseline weight
else if discordance is > 1, take four-year weight
else if baseline weight is missing, take four-year weight
else, take baseline weight
vars_ph_p_dhx_birthweight compute_ph_p_dhx_birthweight( data, name = "ph_p_dhx_birthweight", combine = TRUE )vars_ph_p_dhx_birthweight compute_ph_p_dhx_birthweight( data, name = "ph_p_dhx_birthweight", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. NOTE: Only baseline and year 4 data has been used for this summary score. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_p_dhx_birthweight is a character vector of all column names
used to compute summary score of ph_p_dhx_birthweight.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi_nm
Ohio State Traumatic Brain Injury Screen [Parent]: Number of missing
gating items
Excluded values:
777
999
vars_ph_p_otbi compute_ph_p_otbi_nm( data, name = "ph_p_otbi_nm", exclude = c("777", "999"), combine = TRUE )vars_ph_p_otbi compute_ph_p_otbi_nm( data, name = "ph_p_otbi_nm", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_ph_p_otbi is a character vector of
all column names used to compute summary score of ph_p_otbi_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi__loc__30m_count
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness - Over 30 minutes): Count
Summarized variables:
ph_p_otbi_001
ph_p_otbi__loc_001
ph_p_otbi_002
ph_p_otbi__loc_002
ph_p_otbi_003
ph_p_otbi__loc_003
ph_p_otbi_004
ph_p_otbi__loc_004
ph_p_otbi_005
ph_p_otbi__loc_005
ph_p_otbi__loc__add_001
ph_p_otbi__loc__add_001__03
ph_p_otbi__rpt_001
ph_p_otbi__rpt__loc_001
ph_p_otbi_001__l
ph_p_otbi__loc_001__l
ph_p_otbi_002__l
ph_p_otbi__loc_002__l
ph_p_otbi_003__l
ph_p_otbi__loc_003__l
ph_p_otbi_004__l
ph_p_otbi__loc_004__l
ph_p_otbi_005__l
ph_p_otbi__loc_005__l
ph_p_otbi__loc__add_001__l
ph_p_otbi__loc__add_001__03__l
ph_p_otbi__rpt_001__l
ph_p_otbi__rpt__loc_001__l
Excluded values:
777
999
vars_ph_p_otbi__loc__30m_count compute_ph_p_otbi__loc__30m_count( data, name = "ph_p_otbi__loc__30m_count", exclude = c("777", "999"), combine = TRUE )vars_ph_p_otbi__loc__30m_count compute_ph_p_otbi__loc__30m_count( data, name = "ph_p_otbi__loc__30m_count", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_ph_p_otbi__loc__30m_count is a character vector of all column
names used to compute summary score of ph_p_otbi__loc__30m_count.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi__loc_before15
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): LOC before the age of 15
Summarized variables:
ph_p_otbi_001
ph_p_otbi__loc_001
ph_p_otbi__age_001
ph_p_otbi_002
ph_p_otbi__loc_002
ph_p_otbi__age_002
ph_p_otbi_003
ph_p_otbi__loc_003
ph_p_otbi__age_003
ph_p_otbi_004
ph_p_otbi__loc_004
ph_p_otbi__age_004
ph_p_otbi_005
ph_p_otbi__loc_005
ph_p_otbi__age_005
ph_p_otbi__loc__add_001
ph_p_otbi__loc__add_001__04
ph_p_otbi__rpt_001
ph_p_otbi__rpt__loc_001
ph_p_otbi__rpt__age_001a
ph_p_otbi__rpt_002
ph_p_otbi__rpt__loc__daz_002
ph_p_otbi__rpt__age_002a
ph_p_otbi__rpt_003
ph_p_otbi__rpt__loc__daz_003
ph_p_otbi__rpt__age_003a
ph_p_otbi_001__l
ph_p_otbi__loc_001__l
ph_p_otbi__age_001__l
ph_p_otbi_002__l
ph_p_otbi__loc_002__l
ph_p_otbi__age_002__l
ph_p_otbi_003__l
ph_p_otbi__loc_003__l
ph_p_otbi__age_003__l
ph_p_otbi_004__l
ph_p_otbi__loc_004__l
ph_p_otbi__age_004__l
ph_p_otbi_005__l
ph_p_otbi__loc_005__l
ph_p_otbi__age_005__l
ph_p_otbi__loc__add_001__l
ph_p_otbi__loc__add_001__04__l
ph_p_otbi__rpt_001__l
ph_p_otbi__rpt__loc_001__l
ph_p_otbi__rpt__age_001a__l
Excluded values:
777
999
vars_ph_p_otbi__loc_before15 compute_ph_p_otbi__loc_before15( data, name = "ph_p_otbi__loc_before15", combine = TRUE )vars_ph_p_otbi__loc_before15 compute_ph_p_otbi__loc_before15( data, name = "ph_p_otbi__loc_before15", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
vars_ph_p_otbi__loc_before15 is a character vector of all column
names used to compute summary score of ph_p_otbi__loc_before15.
tbl. The input data frame with the summary score appended as a new column.
compute_ph_p_otbi__loc_tbiage()
Computes the summary score ph_p_otbi__loc_count
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Count
Summarized variables:
ph_p_otbi_001
ph_p_otbi__loc_001
ph_p_otbi_002
ph_p_otbi__loc_002
ph_p_otbi_003
ph_p_otbi__loc_003
ph_p_otbi_004
ph_p_otbi__loc_004
ph_p_otbi_005
ph_p_otbi__loc_005
ph_p_otbi__loc__add_001
ph_p_otbi__loc__add_001__01
ph_p_otbi__rpt_001
ph_p_otbi__rpt__loc_001
ph_p_otbi__rpt_002
ph_p_otbi__rpt__loc__daz_002
ph_p_otbi__rpt_003
ph_p_otbi__rpt__loc__daz_003
ph_p_otbi_001__l
ph_p_otbi__loc_001__l
ph_p_otbi_002__l
ph_p_otbi__loc_002__l
ph_p_otbi_003__l
ph_p_otbi__loc_003__l
ph_p_otbi_004__l
ph_p_otbi__loc_004__l
ph_p_otbi_005__l
ph_p_otbi__loc_005__l
ph_p_otbi__loc__add_001__l
ph_p_otbi__loc__add_001__01__l
ph_p_otbi__rpt_001__l
ph_p_otbi__rpt__loc_001__l
Excluded values:
777
999
vars_ph_p_otbi__loc_count compute_ph_p_otbi__loc_count( data, name = "ph_p_otbi__loc_count", exclude = c("777", "999"), combine = TRUE )vars_ph_p_otbi__loc_count compute_ph_p_otbi__loc_count( data, name = "ph_p_otbi__loc_count", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_ph_p_otbi__loc_count is a character vector of all column names
used to compute summary score of ph_p_otbi__loc_count.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi__loc_tbiage
Ohio State Traumatic Brain Injury Screen [Parent] (Loss of
consciousness): Age of first injury with LOC
Summarized variables:
ph_p_otbi_001
ph_p_otbi__loc_001
ph_p_otbi__age_001
ph_p_otbi_002
ph_p_otbi__loc_002
ph_p_otbi__age_002
ph_p_otbi_003
ph_p_otbi__loc_003
ph_p_otbi__age_003
ph_p_otbi_004
ph_p_otbi__loc_004
ph_p_otbi__age_004
ph_p_otbi_005
ph_p_otbi__loc_005
ph_p_otbi__age_005
ph_p_otbi__loc__add_001
ph_p_otbi__loc__add_001__04
ph_p_otbi__rpt_001
ph_p_otbi__rpt__loc_001
ph_p_otbi__rpt__age_001a
ph_p_otbi__rpt_002
ph_p_otbi__rpt__loc__daz_002
ph_p_otbi__rpt__age_002a
ph_p_otbi__rpt_003
ph_p_otbi__rpt__loc__daz_003
ph_p_otbi__rpt__age_003a
ph_p_otbi_001__l
ph_p_otbi__loc_001__l
ph_p_otbi__age_001__l
ph_p_otbi_002__l
ph_p_otbi__loc_002__l
ph_p_otbi__age_002__l
ph_p_otbi_003__l
ph_p_otbi__loc_003__l
ph_p_otbi__age_003__l
ph_p_otbi_004__l
ph_p_otbi__loc_004__l
ph_p_otbi__age_004__l
ph_p_otbi_005__l
ph_p_otbi__loc_005__l
ph_p_otbi__age_005__l
ph_p_otbi__loc__add_001__l
ph_p_otbi__loc__add_001__04__l
ph_p_otbi__rpt_001__l
ph_p_otbi__rpt__loc_001__l
ph_p_otbi__rpt__age_001a__l
Excluded values:
777
999
any reported age less than or equal to 0
Notes:
The output is set to NA for the following cases:
minimum age is less than 0
minimum age is higher than age at visit
no head or neck injury/impact is reported
vars_ph_p_otbi__loc_tbiage compute_ph_p_otbi__loc_tbiage( data, name = "ph_p_otbi__loc_tbiage", exclude = c("777", "999"), combine = TRUE )vars_ph_p_otbi__loc_tbiage compute_ph_p_otbi__loc_tbiage( data, name = "ph_p_otbi__loc_tbiage", exclude = c("777", "999"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_ph_p_otbi__loc_tbiage is a character vector of all column names
used to compute summary score of ph_p_otbi__loc_tbiage.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi__rpt_count
Ohio State Traumatic Brain Injury Screen [Parent] (Repeated injuries):
Count [Validation: No more than 2 missing or declined at baseline
and no more than 0 missing or declined at non-baseline events]
Summarized variables:
ph_p_otbi__rpt_001
ph_p_otbi__rpt_002
ph_p_otbi__rpt_003
ph_p_otbi__rpt_001__l
Excluded values:
777
999
Validation criterion:
maximally 2 item missing at baseline event
maximally 0 item missing at non-baseline events
vars_ph_p_otbi__rpt_count compute_ph_p_otbi__rpt_count( data, name = "ph_p_otbi__rpt_count", exclude = c("777", "999"), combine = TRUE, max_na = 2 )vars_ph_p_otbi__rpt_count compute_ph_p_otbi__rpt_count( data, name = "ph_p_otbi__rpt_count", exclude = c("777", "999"), combine = TRUE, max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 2). |
vars_ph_p_otbi__rpt_count is a character vector of all column names
used to compute summary score of ph_p_otbi__rpt_count.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_otbi_tbiworst
Ohio State Traumatic Brain Injury Screen [Parent]: Worst injury overall
Summarized variables:
ph_p_otbi_001
ph_p_otbi_002
ph_p_otbi_003
ph_p_otbi_004
ph_p_otbi_005
ph_p_otbi__loc__add_001
ph_p_otbi__rpt_001
ph_p_otbi_001__l
ph_p_otbi_002__l
ph_p_otbi_003__l
ph_p_otbi_004__l
ph_p_otbi_005__l
ph_p_otbi__loc__add_001__l
ph_p_otbi__rpt_001__l
ph_p_otbi__loc_001
ph_p_otbi__loc_002
ph_p_otbi__loc_003
ph_p_otbi__loc_004
ph_p_otbi__loc_005
ph_p_otbi__daz_001
ph_p_otbi__daz_002
ph_p_otbi__daz_003
ph_p_otbi__daz_004
ph_p_otbi__daz_005
ph_p_otbi__rpt__loc_001
ph_p_otbi__rpt__daz_001
ph_p_otbi__rpt_002
ph_p_otbi__rpt__loc__daz_002
ph_p_otbi__rpt_003
ph_p_otbi__rpt__loc__daz_003
ph_p_otbi__loc_001__l
ph_p_otbi__loc_002__l
ph_p_otbi__loc_003__l
ph_p_otbi__loc_004__l
ph_p_otbi__loc_005__l
ph_p_otbi__daz_001__l
ph_p_otbi__daz_002__l
ph_p_otbi__daz_003__l
ph_p_otbi__daz_004__l
ph_p_otbi__daz_005__l
ph_p_otbi__rpt__loc_001__l
ph_p_otbi__rpt__daz_001__l
ph_p_otbi__loc__add_001__02
ph_p_otbi__loc__add_001__03
ph_p_otbi__loc__add_001__02__l
ph_p_otbi__loc__add_001__03__l
Excluded values:
777
999
Notes:
Computed using the following summary scores:
ph_p_otbi__tbi1a
ph_p_otbi__tbi1b
ph_p_otbi__tbi2
ph_p_otbi__tbi3
ph_p_otbi__tbi4
ph_p_otbi__tbi5
vars_ph_p_otbi_tbiworst compute_ph_p_otbi_tbiworst( data, name = "ph_p_otbi_tbiworst", keep_summaries = FALSE, combine = TRUE )vars_ph_p_otbi_tbiworst compute_ph_p_otbi_tbiworst( data, name = "ph_p_otbi_tbiworst", keep_summaries = FALSE, combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
keep_summaries |
logical. If |
combine |
logical. If |
vars_ph_p_otbi_tbiworst is a character vector of all column names
used to compute summary score of ph_p_otbi_tbiworst.
tbl. The input data frame with the summary score(s) appended as a new column.
Computes the summary score ph_p_pds__f_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Mean [Validation: No more than 1 missing or declined]
Summarized variables:
ph_p_pds_001
ph_p_pds_002
ph_p_pds_003
ph_p_pds__f_001
ph_p_pds__f_002
Excluded values:
777
999
Validation criterion: maximally 1 item missing
Notes:
Values in ph_p_pds__f_002 were recoded:
"0" –> "1",
"1" –> "4"
vars_ph_p_pds__f compute_ph_p_pds__f_mean( data, name = "ph_p_pds__f_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )vars_ph_p_pds__f compute_ph_p_pds__f_mean( data, name = "ph_p_pds__f_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_p_pds__f is a character vector of all column names
used to compute summary score of ph_p_pds__f_mean and
ph_p_pds__f_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__f_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Female): Approximate tanner stages [Validation: No more than 0
missing or declined]
Summarized variables:
ph_p_pds_002
ph_p_pds__f_001
ph_p_pds__f_002
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_pds__f_categ compute_ph_p_pds__f_categ( data, name = "ph_p_pds__f_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )vars_ph_p_pds__f_categ compute_ph_p_pds__f_categ( data, name = "ph_p_pds__f_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_p_pds__f is a character vector of all column names
used to compute summary score of ph_p_pds__f_categ and
ph_p_pds__f__categ_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__m_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Mean [Validation: No more than 1 missing or declined]
Summarized variables:
ph_p_pds_001
ph_p_pds_002
ph_p_pds_003
ph_p_pds__m_001
ph_p_pds__m_002
Excluded values:
777
999
Validation criterion: maximally 1 item missing
vars_ph_p_pds__m compute_ph_p_pds__m_mean( data, name = "ph_p_pds__m_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )vars_ph_p_pds__m compute_ph_p_pds__m_mean( data, name = "ph_p_pds__m_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_p_pds__m is a character vector of all column names
used to compute summary score of ph_p_pds__m_mean and
ph_p_pds__m_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_pds__m_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Parent]
(Male): Approximate tanner stages [Validation: No more than 0
missing or declined]
Summarized variables:
ph_p_pds_002
ph_p_pds__m_001
ph_p_pds__m_002
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_pds__m_categ compute_ph_p_pds__m_categ( data, name = "ph_p_pds__m_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )vars_ph_p_pds__m_categ compute_ph_p_pds__m_categ( data, name = "ph_p_pds__m_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_p_pds__m is a character vector of all column names
used to compute summary score of ph_p_pds__m_categ and
ph_p_pds__m__categ_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_p_sds__da_sum
Sleep Disturbance Scale [Parent] (Disorder of arousal): Sum
[Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__da_001
ph_p_sds__da_002
ph_p_sds__da_003
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__da compute_ph_p_sds__da_sum( data, name = "ph_p_sds__da_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__da compute_ph_p_sds__da_sum( data, name = "ph_p_sds__da_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__da_sum and ph_p_sds__da_nm.
## Not run: compute_ph_p_sds__da_sum(data) |> select( all_of(c("ph_p_sds__da_sum", vars_ph_p_sds__da)) ) ## End(Not run)## Not run: compute_ph_p_sds__da_sum(data) |> select( all_of(c("ph_p_sds__da_sum", vars_ph_p_sds__da)) ) ## End(Not run)
Computes the summary score ph_p_sds__dims_sum
Sleep Disturbance Scale [Parent] (Disorders of initiating and maintaining
sleep): Sum [Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__dims_001
ph_p_sds__dims_002
ph_p_sds__dims_003
ph_p_sds__dims_004
ph_p_sds__dims_005
ph_p_sds__dims_006
ph_p_sds__dims_007
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__dims compute_ph_p_sds__dims_sum( data, name = "ph_p_sds__dims_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__dims compute_ph_p_sds__dims_sum( data, name = "ph_p_sds__dims_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__dims_sum and ph_p_sds__dims_nm.
## Not run: compute_ph_p_sds__dims_sum(data) |> select( all_of(c("ph_p_sds__dims_sum", vars_ph_p_sds__dims)) ) ## End(Not run)## Not run: compute_ph_p_sds__dims_sum(data) |> select( all_of(c("ph_p_sds__dims_sum", vars_ph_p_sds__dims)) ) ## End(Not run)
Computes the summary score ph_p_sds__does_sum
Sleep Disturbance Scale [Parent] (Disorders of excessive somnolence): Sum
[Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__does_001
ph_p_sds__does_002
ph_p_sds__does_003
ph_p_sds__does_004
ph_p_sds__does_005
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__does compute_ph_p_sds__does_sum( data, name = "ph_p_sds__does_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__does compute_ph_p_sds__does_sum( data, name = "ph_p_sds__does_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__does_sum and ph_p_sds__does_nm.
## Not run: compute_ph_p_sds__does_sum(data) |> select( all_of(c("ph_p_sds__does_sum", vars_ph_p_sds__does)) ) ## End(Not run)## Not run: compute_ph_p_sds__does_sum(data) |> select( all_of(c("ph_p_sds__does_sum", vars_ph_p_sds__does)) ) ## End(Not run)
Computes the summary score ph_p_sds__hyphy_sum
Sleep Disturbance Scale [Parent] (Sleep hyperhydrosis): Sum
[Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__hyphy_001
ph_p_sds__hyphy_002
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__hyphy compute_ph_p_sds__hyphy_sum( data, name = "ph_p_sds__hyphy_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__hyphy compute_ph_p_sds__hyphy_sum( data, name = "ph_p_sds__hyphy_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__hyphy_sum and ph_p_sds__hyphy_nm.
## Not run: compute_ph_p_sds__hyphy_sum(data) |> select( all_of(c("ph_p_sds__hyphy_sum", vars_ph_p_sds__hyphy)) ) ## End(Not run)## Not run: compute_ph_p_sds__hyphy_sum(data) |> select( all_of(c("ph_p_sds__hyphy_sum", vars_ph_p_sds__hyphy)) ) ## End(Not run)
Computes the summary score ph_p_sds__sbd_sum
Sleep Disturbance Scale [Parent] (Sleep breathing disorders): Sum
[Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__sbd_001
ph_p_sds__sbd_002
ph_p_sds__sbd_003
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__sbd compute_ph_p_sds__sbd_sum( data, name = "ph_p_sds__sbd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__sbd compute_ph_p_sds__sbd_sum( data, name = "ph_p_sds__sbd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__sbd_sum and ph_p_sds__sbd_nm.
## Not run: compute_ph_p_sds__sbd_sum(data) |> select( all_of(c("ph_p_sds__sbd_sum", vars_ph_p_sds__sbd)) ) ## End(Not run)## Not run: compute_ph_p_sds__sbd_sum(data) |> select( all_of(c("ph_p_sds__sbd_sum", vars_ph_p_sds__sbd)) ) ## End(Not run)
Computes the summary score ph_p_sds__swtd_sum
Sleep Disturbance Scale [Parent] (Sleep-wake transition disorders): Sum
[Validation: No more than 0 missing or declined]
Summarized variables:
ph_p_sds__swtd_001
ph_p_sds__swtd_002
ph_p_sds__swtd_003
ph_p_sds__swtd_004
ph_p_sds__swtd_005
ph_p_sds__swtd_006
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds__swtd compute_ph_p_sds__swtd_sum( data, name = "ph_p_sds__swtd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds__swtd compute_ph_p_sds__swtd_sum( data, name = "ph_p_sds__swtd_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds__swtd_sum and ph_p_sds__swtd_nm.
## Not run: compute_ph_p_sds__swtd_sum(data) |> select( all_of(c("ph_p_sds__swtd_sum", vars_ph_p_sds__swtd)) ) ## End(Not run)## Not run: compute_ph_p_sds__swtd_sum(data) |> select( all_of(c("ph_p_sds__swtd_sum", vars_ph_p_sds__swtd)) ) ## End(Not run)
Computes the summary score ph_p_sds_sum
Sleep Disturbance Scale [Parent]: Sum [Validation: No more than 0
missing or declined]
Summarized variables:
ph_p_sds__dims_001
ph_p_sds__dims_002
ph_p_sds__dims_003
ph_p_sds__dims_004
ph_p_sds__dims_005
ph_p_sds__swtd_001
ph_p_sds__swtd_002
ph_p_sds__swtd_003
ph_p_sds__hyphy_001
ph_p_sds__dims_006
ph_p_sds__dims_007
ph_p_sds__swtd_004
ph_p_sds__sbd_001
ph_p_sds__sbd_002
ph_p_sds__sbd_003
ph_p_sds__hyphy_002
ph_p_sds__da_001
ph_p_sds__swtd_005
ph_p_sds__swtd_006
ph_p_sds__da_002
ph_p_sds__da_003
ph_p_sds__does_001
ph_p_sds__does_002
ph_p_sds__does_003
ph_p_sds__does_004
ph_p_sds__does_005
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_p_sds_sum compute_ph_p_sds_sum( data, name = "ph_p_sds_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )vars_ph_p_sds_sum compute_ph_p_sds_sum( data, name = "ph_p_sds_sum", max_na = 0, exclude = c("777", "999"), combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the
summary score. |
exclude |
character, Values to be excluded from the summary score. |
combine |
logical, If |
character vector of all column names
used to compute summary scores of ph_p_sds_sum and ph_p_sds_nm.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_p_sds_sum(data) |> select( all_of(c("ph_p_sds_sum", vars_ph_p_sds_sum)) ) ## End(Not run)## Not run: compute_ph_p_sds_sum(data) |> select( all_of(c("ph_p_sds_sum", vars_ph_p_sds_sum)) ) ## End(Not run)
Computes the summary score ph_y_anthr__height_mean
Anthropometrics [Youth] (Height): Mean
Summarized variables:
ph_y_anthr__height__r01_001
ph_y_anthr__height__r02_001
ph_y_anthr__height__r03_001
Excluded values: none
There are at most 3 possible measurements, and the calculation is as follows:
0 missing, find the max and min of the three, and take the average of the min and max. Then compare the average to the third value.
third value < average -> mean(min, third value)
third value > average -> mean(max, third value)
third value = average -> third value
1 missing, mean of the rest two
2 missing, use the last one
3 missing, NA
vars_ph_y_anthr__height compute_ph_y_anthr__height_mean( data, name = "ph_y_anthr__height_mean", combine = TRUE )vars_ph_y_anthr__height compute_ph_y_anthr__height_mean( data, name = "ph_y_anthr__height_mean", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_y_anthr__height is a character vector of all column names
used to compute summary scores of ph_y_anthr__height.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_anthr__height_mean(data) |> select( all_of(c("ph_y_anthr__height_mean", vars_ph_y_anthr__height)) ) ## End(Not run)## Not run: compute_ph_y_anthr__height_mean(data) |> select( all_of(c("ph_y_anthr__height_mean", vars_ph_y_anthr__height)) ) ## End(Not run)
Computes the summary score ph_y_anthr__weight_mean
Anthropometrics [Youth] (Weight): Mean
Summarized variables: * ph_y_anthr__weight__r01_001
ph_y_anthr__weight__r02_001
ph_y_anthr__weight__r03_001
Excluded values: none
There are at most 3 possible measurements, and the calculation is as follows:
0 missing, find the max and min of the three, and take the average of the min and max. Then compare the average to the third value.
third value < average -> mean(min, third value)
third value > average -> mean(max, third value)
third value = average -> third value
1 missing, mean of the rest two
2 missing, use the last one
3 missing, NA
vars_ph_y_anthr__weight compute_ph_y_anthr__weight_mean( data, name = "ph_y_anthr__weight_mean", combine = TRUE )vars_ph_y_anthr__weight compute_ph_y_anthr__weight_mean( data, name = "ph_y_anthr__weight_mean", combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_y_anthr__weight is a character vector of all column names
used to compute summary scores of ph_y_anthr__weight.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_anthr__weight_mean(data) |> select( all_of(c("ph_y_anthr__weight_mean", vars_ph_y_anthr__weight)) ) ## End(Not run)## Not run: compute_ph_y_anthr__weight_mean(data) |> select( all_of(c("ph_y_anthr__weight_mean", vars_ph_y_anthr__weight)) ) ## End(Not run)
Computes the summary score ph_y_bp__dia_mean
Blood Pressure [Youth] (Diastolic): Mean
Summarized variables:
ph_y_bp__dia__r01_001
ph_y_bp__dia__r01_002
ph_y_bp__dia__r01_003
ph_y_bp__dia__r02_001
ph_y_bp__dia__r02_002
ph_y_bp__dia__r03_001
ph_y_bp__dia__r03_002
Excluded values: none
vars_ph_y_bp__dia compute_ph_y_bp__dia_mean(data, name = "ph_y_bp__dia_mean", combine = TRUE)vars_ph_y_bp__dia compute_ph_y_bp__dia_mean(data, name = "ph_y_bp__dia_mean", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_y_bp__dia is a character vector of all column names
used to compute summary scores of ph_y_bp__dia.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__dia_mean(data) |> select( all_of(c("ph_y_bp__dia_mean", vars_ph_y_bp__dia)) ) ## End(Not run)## Not run: compute_ph_y_bp__dia_mean(data) |> select( all_of(c("ph_y_bp__dia_mean", vars_ph_y_bp__dia)) ) ## End(Not run)
Computes the summary score ph_y_bp__hrate_mean
Blood Pressure [Youth] (Heart rate): Mean
Summarized variables:
ph_y_bp__hrate__r01_001
ph_y_bp__hrate__r01_002
ph_y_bp__hrate__r01_003
ph_y_bp__hrate__r02_001
ph_y_bp__hrate__r02_002
ph_y_bp__hrate__r03_001
ph_y_bp__hrate__r03_002
Excluded values: none
vars_ph_y_bp__hrate compute_ph_y_bp__hrate_mean(data, name = "ph_y_bp__hrate_mean", combine = TRUE)vars_ph_y_bp__hrate compute_ph_y_bp__hrate_mean(data, name = "ph_y_bp__hrate_mean", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_y_bp__hrate is a character vector of all column names
used to compute summary scores of ph_y_bp__hrate.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__hrate_mean(data) |> select( all_of(c("ph_y_bp__hrate_mean", vars_ph_y_bp__hrate)) ) ## End(Not run)## Not run: compute_ph_y_bp__hrate_mean(data) |> select( all_of(c("ph_y_bp__hrate_mean", vars_ph_y_bp__hrate)) ) ## End(Not run)
Computes the summary score ph_y_bp__sys_mean
Blood Pressure [Youth] (Systolic): Mean
Summarized variables:
ph_y_bp__sys__r01_001
ph_y_bp__sys__r01_002
ph_y_bp__sys__r01_003
ph_y_bp__sys__r02_001
ph_y_bp__sys__r02_002
ph_y_bp__sys__r03_001
ph_y_bp__sys__r03_002
Excluded values: none
vars_ph_y_bp__sys compute_ph_y_bp__sys_mean(data, name = "ph_y_bp__sys_mean", combine = TRUE)vars_ph_y_bp__sys compute_ph_y_bp__sys_mean(data, name = "ph_y_bp__sys_mean", combine = TRUE)
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
vars_ph_y_bp__sys is a character vector of all column names
used to compute summary scores of ph_y_bp__sys.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_ph_y_bp__sys_mean(data) |> select( all_of(c("ph_y_bp__sys_mean", vars_ph_y_bp__sys)) ) ## End(Not run)## Not run: compute_ph_y_bp__sys_mean(data) |> select( all_of(c("ph_y_bp__sys_mean", vars_ph_y_bp__sys)) ) ## End(Not run)
Computes the summary score ph_y_pds__f_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Mean [Validation: No more than 1 missing or declined]
Summarized variables:
ph_y_pds_001
ph_y_pds_002
ph_y_pds_003
ph_y_pds__f_001
ph_y_pds__f_002
Excluded values:
777
999
Validation criterion: maximally 1 item missing
vars_ph_y_pds__f compute_ph_y_pds__f_mean( data, name = "ph_y_pds__f_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )vars_ph_y_pds__f compute_ph_y_pds__f_mean( data, name = "ph_y_pds__f_mean", exclude = c("777", "999"), combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_y_pds__f is a character vector of all column names
used to compute summary score of ph_y_pds__f_mean and
ph_y_pds__f_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__f_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Female): Approximate tanner stages [Validation: No more than 0
missing or declined]
Summarized variables:
ph_y_pds_002
ph_y_pds__f_001
ph_y_pds__f_002
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_y_pds__f_categ compute_ph_y_pds__f_categ( data, name = "ph_y_pds__f_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )vars_ph_y_pds__f_categ compute_ph_y_pds__f_categ( data, name = "ph_y_pds__f_categ", exclude = c("777", "999"), combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_y_pds__f is a character vector of all column names
used to compute summary score of ph_y_pds__f_categ and
ph_y_pds__f__categ_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__m_mean
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Mean [Validation: No more than 1 missing or declined]
Summarized variables:
ph_y_pds_001
ph_y_pds_002
ph_y_pds_003
ph_y_pds__m_001
ph_y_pds__m_002
Excluded values:
777
999
Validation criterion: maximally 1 item missing
vars_ph_y_pds__m compute_ph_y_pds__m_mean( data, name = "ph_y_pds__m_mean", combine = TRUE, exclude = c("777", "999"), max_na = 1 )vars_ph_y_pds__m compute_ph_y_pds__m_mean( data, name = "ph_y_pds__m_mean", combine = TRUE, exclude = c("777", "999"), max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_y_pds__m is a character vector of all column names
used to compute summary score of ph_y_pds__m_mean and
ph_y_pds__m_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score ph_y_pds__m_categ
Pubertal Development Scale & Menstrual Cycle Survey History [Youth]
(Male): Approximate tanner stages [Validation: No more than 0
missing or declined]
Summarized variables:
ph_y_pds_002
ph_y_pds__m_001
ph_y_pds__m_002
Excluded values:
777
999
Validation criterion: maximally 0 items missing
vars_ph_y_pds__m_categ compute_ph_y_pds__m_categ( data, name = "ph_y_pds__m_categ", combine = TRUE, exclude = c("777", "999"), max_na = 0 )vars_ph_y_pds__m_categ compute_ph_y_pds__m_categ( data, name = "ph_y_pds__m_categ", combine = TRUE, exclude = c("777", "999"), max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
combine |
logical. If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
vars_ph_y_pds__m is a character vector of all column names
used to compute summary score of ph_y_pds__m_categ and
ph_y_pds__m__categ_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_p_ksads__aud__past__sx_mean
KSADS - Alcohol Use Disorder [Parent] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_p_ksads__aud__actvdecr__past_sx
su_p_ksads__aud__crave__past_sx
su_p_ksads__aud__dwi__past_sx
su_p_ksads__aud__failrespons__past_sx
su_p_ksads__aud__haz__past_sx
su_p_ksads__aud__negimpct__interprs__past_sx
su_p_ksads__aud__overuse__past_sx
su_p_ksads__aud__prob__phys__past_sx
su_p_ksads__aud__prob__psych__past_sx
su_p_ksads__aud__reduce__dsr__past_sx
su_p_ksads__aud__reduce__unsucces__past_sx
su_p_ksads__aud__time__past_sx
su_p_ksads__aud__tol__past_sx
su_p_ksads__aud__withdr__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_p_ksads__aud__past__sx compute_su_p_ksads__aud__past__sx_mean( data, name = "su_p_ksads__aud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_p_ksads__aud__past__sx compute_su_p_ksads__aud__past__sx_mean( data, name = "su_p_ksads__aud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__aud__past__sx is a character vector
of all column names used to compute summary score of
su_p_ksads__aud__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__aud__pres__sx_mean
KSADS - Alcohol Use Disorder [Parent] (Symptom - Present): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_p_ksads__aud__actvdecr__pres_sx
su_p_ksads__aud__crave__pres_sx
su_p_ksads__aud__dwi__pres_sx
su_p_ksads__aud__failrespons__pres_sx
su_p_ksads__aud__haz__pres_sx
su_p_ksads__aud__negimpct__interprs__pres_sx
su_p_ksads__aud__overuse__pres_sx
su_p_ksads__aud__prob__phys__pres_sx
su_p_ksads__aud__prob__psych__pres_sx
su_p_ksads__aud__reduce__dsr__pres_sx
su_p_ksads__aud__reduce__unsucces__pres_sx
su_p_ksads__aud__time__pres_sx
su_p_ksads__aud__tol__pres_sx
su_p_ksads__aud__withdr__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_p_ksads__aud__pres__sx compute_su_p_ksads__aud__pres__sx_mean( data, name = "su_p_ksads__aud__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_p_ksads__aud__pres__sx compute_su_p_ksads__aud__pres__sx_mean( data, name = "su_p_ksads__aud__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__aud__pres__sx is a character vector
of all column names used to compute summary score of
su_p_ksads__aud__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__coc__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Cocaine - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__coc__past_sx
su_p_ksads__dud__crave__coc__past_sx
su_p_ksads__dud__dwi__coc__past_sx
su_p_ksads__dud__failrespons__coc__past_sx
su_p_ksads__dud__haz__coc__past_sx
su_p_ksads__dud__negimpct__interprs__coc__past_sx
su_p_ksads__dud__negimpct__obl__coc__past_sx
su_p_ksads__dud__overuse__coc__past_sx
su_p_ksads__dud__prob__phys__coc__past_sx
su_p_ksads__dud__prob__psych__coc__past_sx
su_p_ksads__dud__reduce__dsr__coc__past_sx
su_p_ksads__dud__reduce__unsucces__coc__past_sx
su_p_ksads__dud__time__coc__past_sx
su_p_ksads__dud__tol__coc__past_sx
su_p_ksads__dud__withdr__coc__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__coc__past__sx_mean compute_su_p_ksads__dud__coc__past__sx_mean( data, name = "su_p_ksads__dud__coc__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__coc__past__sx_mean compute_su_p_ksads__dud__coc__past__sx_mean( data, name = "su_p_ksads__dud__coc__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__coc__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__coc__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__coc__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Cocaine - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__coc__pres_sx
su_p_ksads__dud__crave__coc__pres_sx
su_p_ksads__dud__dwi__coc__pres_sx
su_p_ksads__dud__failrespons__coc__pres_sx
su_p_ksads__dud__haz__coc__pres_sx
su_p_ksads__dud__negimpct__interprs__coc__pres_sx
su_p_ksads__dud__negimpct__obl__coc__pres_sx
su_p_ksads__dud__overuse__coc__pres_sx
su_p_ksads__dud__prob__phys__coc__pres_sx
su_p_ksads__dud__prob__psych__coc__pres_sx
su_p_ksads__dud__reduce__dsr__coc__pres_sx
su_p_ksads__dud__reduce__unsucces__coc__pres_sx
su_p_ksads__dud__time__coc__pres_sx
su_p_ksads__dud__tol__coc__pres_sx
su_p_ksads__dud__withdr__coc__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__coc__pres__sx_mean compute_su_p_ksads__dud__coc__pres__sx_mean( data, name = "su_p_ksads__dud__coc__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__coc__pres__sx_mean compute_su_p_ksads__dud__coc__pres__sx_mean( data, name = "su_p_ksads__dud__coc__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__coc__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__coc__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__hall__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Hallucinogen - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__hall__past_sx
su_p_ksads__dud__crave__hall__past_sx
su_p_ksads__dud__dwi__hall__past_sx
su_p_ksads__dud__failrespons__hall__past_sx
su_p_ksads__dud__haz__hall__past_sx
su_p_ksads__dud__negimpct__interprs__hall__past_sx
su_p_ksads__dud__negimpct__obl__hall__past_sx
su_p_ksads__dud__overuse__hall__past_sx
su_p_ksads__dud__prob__phys__hall__past_sx
su_p_ksads__dud__prob__psych__hall__past_sx
su_p_ksads__dud__reduce__dsr__hall__past_sx
su_p_ksads__dud__reduce__unsucces__hall__past_sx
su_p_ksads__dud__time__hall__past_sx
su_p_ksads__dud__tol__hall__past_sx
su_p_ksads__dud__withdr__hall__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__hall__past__sx_mean compute_su_p_ksads__dud__hall__past__sx_mean( data, name = "su_p_ksads__dud__hall__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__hall__past__sx_mean compute_su_p_ksads__dud__hall__past__sx_mean( data, name = "su_p_ksads__dud__hall__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__hall__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__hall__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__hall__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Hallucinogen - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__hall__pres_sx
su_p_ksads__dud__crave__hall__pres_sx
su_p_ksads__dud__dwi__hall__pres_sx
su_p_ksads__dud__failrespons__hall__pres_sx
su_p_ksads__dud__haz__hall__pres_sx
su_p_ksads__dud__negimpct__interprs__hall__pres_sx
su_p_ksads__dud__negimpct__obl__hall__pres_sx
su_p_ksads__dud__overuse__hall__pres_sx
su_p_ksads__dud__prob__phys__hall__pres_sx
su_p_ksads__dud__prob__psych__hall__pres_sx
su_p_ksads__dud__reduce__dsr__hall__pres_sx
su_p_ksads__dud__reduce__unsucces__hall__pres_sx
su_p_ksads__dud__time__hall__pres_sx
su_p_ksads__dud__tol__hall__pres_sx
su_p_ksads__dud__withdr__hall__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__hall__pres__sx_mean compute_su_p_ksads__dud__hall__pres__sx_mean( data, name = "su_p_ksads__dud__hall__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__hall__pres__sx_mean compute_su_p_ksads__dud__hall__pres__sx_mean( data, name = "su_p_ksads__dud__hall__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__hall__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__hall__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__mj__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Cannabis - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__mj__past_sx
su_p_ksads__dud__crave__mj__past_sx
su_p_ksads__dud__dwi__mj__past_sx
su_p_ksads__dud__failrespons__mj__past_sx
su_p_ksads__dud__haz__mj__past_sx
su_p_ksads__dud__negimpct__interprs__mj__past_sx
su_p_ksads__dud__negimpct__obl__mj__past_sx
su_p_ksads__dud__overuse__mj__past_sx
su_p_ksads__dud__prob__phys__mj__past_sx
su_p_ksads__dud__prob__psych__mj__past_sx
su_p_ksads__dud__reduce__dsr__mj__past_sx
su_p_ksads__dud__reduce__unsucces__mj__past_sx
su_p_ksads__dud__time__mj__past_sx
su_p_ksads__dud__tol__mj__past_sx
su_p_ksads__dud__withdr__mj__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__mj__past__sx_mean compute_su_p_ksads__dud__mj__past__sx_mean( data, name = "su_p_ksads__dud__mj__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__mj__past__sx_mean compute_su_p_ksads__dud__mj__past__sx_mean( data, name = "su_p_ksads__dud__mj__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__mj__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__mj__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__mj__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Cannabis - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__mj__pres_sx
su_p_ksads__dud__crave__mj__pres_sx
su_p_ksads__dud__dwi__mj__pres_sx
su_p_ksads__dud__failrespons__mj__pres_sx
su_p_ksads__dud__haz__mj__pres_sx
su_p_ksads__dud__negimpct__interprs__mj__pres_sx
su_p_ksads__dud__negimpct__obl__mj__pres_sx
su_p_ksads__dud__overuse__mj__pres_sx
su_p_ksads__dud__prob__phys__mj__pres_sx
su_p_ksads__dud__prob__psych__mj__pres_sx
su_p_ksads__dud__reduce__dsr__mj__pres_sx
su_p_ksads__dud__reduce__unsucces__mj__pres_sx
su_p_ksads__dud__time__mj__pres_sx
su_p_ksads__dud__tol__mj__pres_sx
su_p_ksads__dud__withdr__mj__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__mj__pres__sx_mean compute_su_p_ksads__dud__mj__pres__sx_mean( data, name = "su_p_ksads__dud__mj__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__mj__pres__sx_mean compute_su_p_ksads__dud__mj__pres__sx_mean( data, name = "su_p_ksads__dud__mj__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__mj__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__mj__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__nic__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Tobacco - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__nic__past_sx
su_p_ksads__dud__crave__nic__past_sx
su_p_ksads__dud__dwi__nic__past_sx
su_p_ksads__dud__failrespons__nic__past_sx
su_p_ksads__dud__haz__nic__past_sx
su_p_ksads__dud__negimpct__interprs__nic__past_sx
su_p_ksads__dud__negimpct__obl__nic__past_sx
su_p_ksads__dud__overuse__nic__past_sx
su_p_ksads__dud__prob__phys__nic__past_sx
su_p_ksads__dud__prob__psych__nic__past_sx
su_p_ksads__dud__reduce__dsr__nic__past_sx
su_p_ksads__dud__reduce__unsucces__nic__past_sx
su_p_ksads__dud__time__nic__past_sx
su_p_ksads__dud__tol__nic__past_sx
su_p_ksads__dud__withdr__nic__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__nic__past__sx_mean compute_su_p_ksads__dud__nic__past__sx_mean( data, name = "su_p_ksads__dud__nic__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__nic__past__sx_mean compute_su_p_ksads__dud__nic__past__sx_mean( data, name = "su_p_ksads__dud__nic__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__nic__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__nic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__nic__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Tobacco - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__nic__pres_sx
su_p_ksads__dud__crave__nic__pres_sx
su_p_ksads__dud__dwi__nic__pres_sx
su_p_ksads__dud__failrespons__nic__pres_sx
su_p_ksads__dud__haz__nic__pres_sx
su_p_ksads__dud__negimpct__interprs__nic__pres_sx
su_p_ksads__dud__negimpct__obl__nic__pres_sx
su_p_ksads__dud__overuse__nic__pres_sx
su_p_ksads__dud__prob__phys__nic__pres_sx
su_p_ksads__dud__prob__psych__nic__pres_sx
su_p_ksads__dud__reduce__dsr__nic__pres_sx
su_p_ksads__dud__reduce__unsucces__nic__pres_sx
su_p_ksads__dud__time__nic__pres_sx
su_p_ksads__dud__tol__nic__pres_sx
su_p_ksads__dud__withdr__nic__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__nic__pres__sx_mean compute_su_p_ksads__dud__nic__pres__sx_mean( data, name = "su_p_ksads__dud__nic__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__nic__pres__sx_mean compute_su_p_ksads__dud__nic__pres__sx_mean( data, name = "su_p_ksads__dud__nic__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__nic__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__nic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__opi__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Opiod - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__opi__past_sx
su_p_ksads__dud__crave__opi__past_sx
su_p_ksads__dud__dwi__opi__past_sx
su_p_ksads__dud__failrespons__opi__past_sx
su_p_ksads__dud__haz__opi__past_sx
su_p_ksads__dud__negimpct__interprs__opi__past_sx
su_p_ksads__dud__negimpct__obl__opi__past_sx
su_p_ksads__dud__overuse__opi__past_sx
su_p_ksads__dud__prob__phys__opi__past_sx
su_p_ksads__dud__prob__psych__opi__past_sx
su_p_ksads__dud__reduce__dsr__opi__past_sx
su_p_ksads__dud__reduce__unsucces__opi__past_sx
su_p_ksads__dud__time__opi__past_sx
su_p_ksads__dud__tol__opi__past_sx
su_p_ksads__dud__withdr__opi__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__opi__past__sx_mean compute_su_p_ksads__dud__opi__past__sx_mean( data, name = "su_p_ksads__dud__opi__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__opi__past__sx_mean compute_su_p_ksads__dud__opi__past__sx_mean( data, name = "su_p_ksads__dud__opi__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__opi__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__opi__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__opi__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Opiod - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__opi__pres_sx
su_p_ksads__dud__crave__opi__pres_sx
su_p_ksads__dud__dwi__opi__pres_sx
su_p_ksads__dud__failrespons__opi__pres_sx
su_p_ksads__dud__haz__opi__pres_sx
su_p_ksads__dud__negimpct__interprs__opi__pres_sx
su_p_ksads__dud__negimpct__obl__opi__pres_sx
su_p_ksads__dud__overuse__opi__pres_sx
su_p_ksads__dud__prob__phys__opi__pres_sx
su_p_ksads__dud__prob__psych__opi__pres_sx
su_p_ksads__dud__reduce__dsr__opi__pres_sx
su_p_ksads__dud__reduce__unsucces__opi__pres_sx
su_p_ksads__dud__time__opi__pres_sx
su_p_ksads__dud__tol__opi__pres_sx
su_p_ksads__dud__withdr__opi__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__opi__pres__sx_mean compute_su_p_ksads__dud__opi__pres__sx_mean( data, name = "su_p_ksads__dud__opi__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__opi__pres__sx_mean compute_su_p_ksads__dud__opi__pres__sx_mean( data, name = "su_p_ksads__dud__opi__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__opi__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__opi__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__othdrg__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Other drugs - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__othdrg__past_sx
su_p_ksads__dud__crave__othdrg__past_sx
su_p_ksads__dud__dwi__othdrg__past_sx
su_p_ksads__dud__failrespons__othdrg__past_sx
su_p_ksads__dud__haz__othdrg__past_sx
su_p_ksads__dud__negimpct__interprs__othdrg__past_sx
su_p_ksads__dud__negimpct__obl__othdrg__past_sx
su_p_ksads__dud__overuse__othdrg__past_sx
su_p_ksads__dud__prob__phys__othdrg__past_sx
su_p_ksads__dud__prob__psych__othdrg__past_sx
su_p_ksads__dud__reduce__dsr__othdrg__past_sx
su_p_ksads__dud__reduce__unsucces__othdrg__past_sx
su_p_ksads__dud__time__othdrg__past_sx
su_p_ksads__dud__tol__othdrg__past_sx
su_p_ksads__dud__withdr__othdrg__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__othdrg__past__sx_mean compute_su_p_ksads__dud__othdrg__past__sx_mean( data, name = "su_p_ksads__dud__othdrg__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__othdrg__past__sx_mean compute_su_p_ksads__dud__othdrg__past__sx_mean( data, name = "su_p_ksads__dud__othdrg__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__othdrg__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__othdrg__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__othdrg__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Other drugs - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__othdrg__pres_sx
su_p_ksads__dud__crave__othdrg__pres_sx
su_p_ksads__dud__dwi__othdrg__pres_sx
su_p_ksads__dud__failrespons__othdrg__pres_sx
su_p_ksads__dud__haz__othdrg__pres_sx
su_p_ksads__dud__negimpct__interprs__othdrg__pres_sx
su_p_ksads__dud__negimpct__obl__othdrg__pres_sx
su_p_ksads__dud__overuse__othdrg__pres_sx
su_p_ksads__dud__prob__phys__othdrg__pres_sx
su_p_ksads__dud__prob__psych__othdrg__pres_sx
su_p_ksads__dud__reduce__dsr__othdrg__pres_sx
su_p_ksads__dud__reduce__unsucces__othdrg__pres_sx
su_p_ksads__dud__time__othdrg__pres_sx
su_p_ksads__dud__tol__othdrg__pres_sx
su_p_ksads__dud__withdr__othdrg__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__othdrg__pres__sx_mean compute_su_p_ksads__dud__othdrg__pres__sx_mean( data, name = "su_p_ksads__dud__othdrg__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__othdrg__pres__sx_mean compute_su_p_ksads__dud__othdrg__pres__sx_mean( data, name = "su_p_ksads__dud__othdrg__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__othdrg__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__othdrg__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__past_sx
su_p_ksads__dud__crave__past_sx
su_p_ksads__dud__dwi__past_sx
su_p_ksads__dud__failrespons__past_sx
su_p_ksads__dud__haz__past_sx
su_p_ksads__dud__negimpct__interprs__past_sx
su_p_ksads__dud__negimpct__obl__past_sx
su_p_ksads__dud__overuse__past_sx
su_p_ksads__dud__prob__phys__past_sx
su_p_ksads__dud__prob__psych__past_sx
su_p_ksads__dud__reduce__dsr__past_sx
su_p_ksads__dud__reduce__unsucces__past_sx
su_p_ksads__dud__tol__past_sx
su_p_ksads__dud__withdr__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_p_ksads__dud__past__sx_mean compute_su_p_ksads__dud__past__sx_mean( data, name = "su_p_ksads__dud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__past__sx_mean compute_su_p_ksads__dud__past__sx_mean( data, name = "su_p_ksads__dud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__pcp__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: PCP - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__pcp__past_sx
su_p_ksads__dud__crave__pcp__past_sx
su_p_ksads__dud__dwi__pcp__past_sx
su_p_ksads__dud__failrespons__pcp__past_sx
su_p_ksads__dud__haz__pcp__past_sx
su_p_ksads__dud__negimpct__interprs__pcp__past_sx
su_p_ksads__dud__negimpct__obl__pcp__past_sx
su_p_ksads__dud__overuse__pcp__past_sx
su_p_ksads__dud__prob__phys__pcp__past_sx
su_p_ksads__dud__prob__psych__pcp__past_sx
su_p_ksads__dud__reduce__dsr__pcp__past_sx
su_p_ksads__dud__reduce__unsucces__pcp__past_sx
su_p_ksads__dud__time__pcp__past_sx
su_p_ksads__dud__tol__pcp__past_sx
su_p_ksads__dud__withdr__pcp__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__pcp__past__sx_mean compute_su_p_ksads__dud__pcp__past__sx_mean( data, name = "su_p_ksads__dud__pcp__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__pcp__past__sx_mean compute_su_p_ksads__dud__pcp__past__sx_mean( data, name = "su_p_ksads__dud__pcp__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__pcp__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__pcp__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__pcp__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: PCP - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__pcp__pres_sx
su_p_ksads__dud__crave__pcp__pres_sx
su_p_ksads__dud__dwi__pcp__pres_sx
su_p_ksads__dud__failrespons__pcp__pres_sx
su_p_ksads__dud__haz__pcp__pres_sx
su_p_ksads__dud__negimpct__interprs__pcp__pres_sx
su_p_ksads__dud__negimpct__obl__pcp__pres_sx
su_p_ksads__dud__overuse__pcp__pres_sx
su_p_ksads__dud__prob__phys__pcp__pres_sx
su_p_ksads__dud__prob__psych__pcp__pres_sx
su_p_ksads__dud__reduce__dsr__pcp__pres_sx
su_p_ksads__dud__reduce__unsucces__pcp__pres_sx
su_p_ksads__dud__time__pcp__pres_sx
su_p_ksads__dud__tol__pcp__pres_sx
su_p_ksads__dud__withdr__pcp__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__pcp__pres__sx_mean compute_su_p_ksads__dud__pcp__pres__sx_mean( data, name = "su_p_ksads__dud__pcp__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__pcp__pres__sx_mean compute_su_p_ksads__dud__pcp__pres__sx_mean( data, name = "su_p_ksads__dud__pcp__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__pcp__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__pcp__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__pres_sx
su_p_ksads__dud__crave__pres_sx
su_p_ksads__dud__dwi__pres_sx
su_p_ksads__dud__failrespons__pres_sx
su_p_ksads__dud__haz__pres_sx
su_p_ksads__dud__negimpct__interprs__pres_sx
su_p_ksads__dud__negimpct__obl__pres_sx
su_p_ksads__dud__overuse__pres_sx
su_p_ksads__dud__prob__phys__pres_sx
su_p_ksads__dud__prob__psych__pres_sx
su_p_ksads__dud__reduce__dsr__pres_sx
su_p_ksads__dud__reduce__unsucces__pres_sx
su_p_ksads__dud__time__pres_sx
su_p_ksads__dud__tol__pres_sx
su_p_ksads__dud__withdr__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__pres__sx_mean compute_su_p_ksads__dud__pres__sx_mean( data, name = "su_p_ksads__dud__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__pres__sx_mean compute_su_p_ksads__dud__pres__sx_mean( data, name = "su_p_ksads__dud__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__sed__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Sedatives - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__sed__past_sx
su_p_ksads__dud__crave__sed__past_sx
su_p_ksads__dud__dwi__sed__past_sx
su_p_ksads__dud__failrespons__sed__past_sx
su_p_ksads__dud__haz__sed__past_sx
su_p_ksads__dud__negimpct__interprs__sed__past_sx
su_p_ksads__dud__negimpct__obl__sed__past_sx
su_p_ksads__dud__overuse__sed__past_sx
su_p_ksads__dud__prob__phys__sed__past_sx
su_p_ksads__dud__prob__psych__sed__past_sx
su_p_ksads__dud__reduce__dsr__sed__past_sx
su_p_ksads__dud__reduce__unsucces__sed__past_sx
su_p_ksads__dud__time__sed__past_sx
su_p_ksads__dud__tol__sed__past_sx
su_p_ksads__dud__withdr__sed__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__sed__past__sx_mean compute_su_p_ksads__dud__sed__past__sx_mean( data, name = "su_p_ksads__dud__sed__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__sed__past__sx_mean compute_su_p_ksads__dud__sed__past__sx_mean( data, name = "su_p_ksads__dud__sed__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__sed__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__sed__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__sed__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Sedatives - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__sed__pres_sx
su_p_ksads__dud__crave__sed__pres_sx
su_p_ksads__dud__dwi__sed__pres_sx
su_p_ksads__dud__failrespons__sed__pres_sx
su_p_ksads__dud__haz__sed__pres_sx
su_p_ksads__dud__negimpct__interprs__sed__pres_sx
su_p_ksads__dud__negimpct__obl__sed__pres_sx
su_p_ksads__dud__overuse__sed__pres_sx
su_p_ksads__dud__prob__phys__sed__pres_sx
su_p_ksads__dud__prob__psych__sed__pres_sx
su_p_ksads__dud__reduce__dsr__sed__pres_sx
su_p_ksads__dud__reduce__unsucces__sed__pres_sx
su_p_ksads__dud__time__sed__pres_sx
su_p_ksads__dud__tol__sed__pres_sx
su_p_ksads__dud__withdr__sed__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__sed__pres__sx_mean compute_su_p_ksads__dud__sed__pres__sx_mean( data, name = "su_p_ksads__dud__sed__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__sed__pres__sx_mean compute_su_p_ksads__dud__sed__pres__sx_mean( data, name = "su_p_ksads__dud__sed__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__sed__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__sed__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__solv__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Solvent - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__solv__past_sx
su_p_ksads__dud__crave__solv__past_sx
su_p_ksads__dud__dwi__solv__past_sx
su_p_ksads__dud__failrespons__solv__past_sx
su_p_ksads__dud__haz__solv__past_sx
su_p_ksads__dud__negimpct__interprs__solv__past_sx
su_p_ksads__dud__negimpct__obl__solv__past_sx
su_p_ksads__dud__overuse__solv__past_sx
su_p_ksads__dud__prob__phys__solv__past_sx
su_p_ksads__dud__prob__psych__solv__past_sx
su_p_ksads__dud__reduce__dsr__solv__past_sx
su_p_ksads__dud__reduce__unsucces__solv__past_sx
su_p_ksads__dud__time__solv__past_sx
su_p_ksads__dud__tol__solv__past_sx
su_p_ksads__dud__withdr__solv__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__solv__past__sx_mean compute_su_p_ksads__dud__solv__past__sx_mean( data, name = "su_p_ksads__dud__solv__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__solv__past__sx_mean compute_su_p_ksads__dud__solv__past__sx_mean( data, name = "su_p_ksads__dud__solv__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__solv__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__solv__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__solv__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Solvent - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__solv__pres_sx
su_p_ksads__dud__crave__solv__pres_sx
su_p_ksads__dud__dwi__solv__pres_sx
su_p_ksads__dud__failrespons__solv__pres_sx
su_p_ksads__dud__haz__solv__pres_sx
su_p_ksads__dud__negimpct__interprs__solv__pres_sx
su_p_ksads__dud__negimpct__obl__solv__pres_sx
su_p_ksads__dud__overuse__solv__pres_sx
su_p_ksads__dud__prob__phys__solv__pres_sx
su_p_ksads__dud__prob__psych__solv__pres_sx
su_p_ksads__dud__reduce__dsr__solv__pres_sx
su_p_ksads__dud__reduce__unsucces__solv__pres_sx
su_p_ksads__dud__time__solv__pres_sx
su_p_ksads__dud__tol__solv__pres_sx
su_p_ksads__dud__withdr__solv__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__solv__pres__sx_mean compute_su_p_ksads__dud__solv__pres__sx_mean( data, name = "su_p_ksads__dud__solv__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__solv__pres__sx_mean compute_su_p_ksads__dud__solv__pres__sx_mean( data, name = "su_p_ksads__dud__solv__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__solv__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__solv__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__stim__past__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Stimulants - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__stim__past_sx
su_p_ksads__dud__crave__stim__past_sx
su_p_ksads__dud__dwi__stim__past_sx
su_p_ksads__dud__failrespons__stim__past_sx
su_p_ksads__dud__haz__stim__past_sx
su_p_ksads__dud__negimpct__interprs__stim__past_sx
su_p_ksads__dud__negimpct__obl__stim__past_sx
su_p_ksads__dud__overuse__stim__past_sx
su_p_ksads__dud__prob__phys__stim__past_sx
su_p_ksads__dud__prob__psych__stim__past_sx
su_p_ksads__dud__reduce__dsr__stim__past_sx
su_p_ksads__dud__reduce__unsucces__stim__past_sx
su_p_ksads__dud__time__stim__past_sx
su_p_ksads__dud__tol__stim__past_sx
su_p_ksads__dud__withdr__stim__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__stim__past__sx_mean compute_su_p_ksads__dud__stim__past__sx_mean( data, name = "su_p_ksads__dud__stim__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__stim__past__sx_mean compute_su_p_ksads__dud__stim__past__sx_mean( data, name = "su_p_ksads__dud__stim__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__stim__past__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__stim__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_p_ksads__dud__stim__pres__sx_mean
KSADS - Drug Use Disorders [Parent] (Symptom: Stimulants - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_p_ksads__dud__actvdecr__stim__pres_sx
su_p_ksads__dud__crave__stim__pres_sx
su_p_ksads__dud__dwi__stim__pres_sx
su_p_ksads__dud__failrespons__stim__pres_sx
su_p_ksads__dud__haz__stim__pres_sx
su_p_ksads__dud__negimpct__interprs__stim__pres_sx
su_p_ksads__dud__negimpct__obl__stim__pres_sx
su_p_ksads__dud__overuse__stim__pres_sx
su_p_ksads__dud__prob__phys__stim__pres_sx
su_p_ksads__dud__prob__psych__stim__pres_sx
su_p_ksads__dud__reduce__dsr__stim__pres_sx
su_p_ksads__dud__reduce__unsucces__stim__pres_sx
su_p_ksads__dud__time__stim__pres_sx
su_p_ksads__dud__tol__stim__pres_sx
su_p_ksads__dud__withdr__stim__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_p_ksads__dud__stim__pres__sx_mean compute_su_p_ksads__dud__stim__pres__sx_mean( data, name = "su_p_ksads__dud__stim__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_p_ksads__dud__stim__pres__sx_mean compute_su_p_ksads__dud__stim__pres__sx_mean( data, name = "su_p_ksads__dud__stim__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_p_ksads__dud__stim__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_p_ksads__dud__stim__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_alcexp__neg_prsum
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of negative
expectancies): Prorated sum
Summarized variables:
su_y_alcexp__neg_001
su_y_alcexp__neg_002
su_y_alcexp__neg_003
Excluded values: none
Validation criterion: maximally 1 of 3 items missing
vars_su_y_alcexp__neg compute_su_y_alcexp__neg_prsum( data, name = "su_y_alcexp__neg_prsum", combine = TRUE, max_na = 1 )vars_su_y_alcexp__neg compute_su_y_alcexp__neg_prsum( data, name = "su_y_alcexp__neg_prsum", combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_alcexp__neg is a character vector of all column names
used to compute summary score of su_y_alcexp__neg_prsum and
su_y_alcexp__neg_nm
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcexp__pos_prsum
Alcohol Expectancies (AEQ-AB) [Youth] (Strength of positive
expectancies): Prorated sum
Summarized variables:
su_y_alcexp__pos_001
su_y_alcexp__pos_002
su_y_alcexp__pos_003
Excluded values: none
Validation criterion: maximally 1 of 3 items missing
vars_su_y_alcexp__pos compute_su_y_alcexp__pos_prsum( data, name = "su_y_alcexp__pos_prsum", combine = TRUE, max_na = 1 )vars_su_y_alcexp__pos compute_su_y_alcexp__pos_prsum( data, name = "su_y_alcexp__pos_prsum", combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_alcexp__pos is a character vector of all column names
used to compute summary score of su_y_alcexp__pos_prsum and
su_y_alcexp__pos_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alchss_sum
Alcohol Hangover Symptoms Scale (HSS) [Youth]: Sum
Summarized variables:
su_y_alchss_001
su_y_alchss_002
su_y_alchss_003
su_y_alchss_004
su_y_alchss_005
su_y_alchss_006
su_y_alchss_007
su_y_alchss_008
su_y_alchss_009
su_y_alchss_010
su_y_alchss_011
su_y_alchss_012
su_y_alchss_013
su_y_alchss_014
su_y_alchss_001__l
su_y_alchss_002__l
su_y_alchss_003__l
su_y_alchss_004__l
su_y_alchss_005__l
su_y_alchss_006__l
su_y_alchss_007__l
su_y_alchss_008__l
su_y_alchss_009__l
su_y_alchss_010__l
su_y_alchss_011__l
su_y_alchss_012__l
su_y_alchss_013__l
su_y_alchss_014__l
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
vars_su_y_alchss compute_su_y_alchss_sum( data, name = "su_y_alchss_sum", max_na = 0, combine = TRUE )vars_su_y_alchss compute_su_y_alchss_sum( data, name = "su_y_alchss_sum", max_na = 0, combine = TRUE )
data |
tbl, Dataframe containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
max_na |
integer, Maximum number of missing values allowed in the summary score. |
combine |
logical, If |
vars_su_y_alchss is a table of all column names
used to compute summary score of su_y_alchss.
tbl. The input data frame with the summary score appended as a new column.
## Not run: compute_su_y_alchss_sum(data) ## End(Not run)## Not run: compute_su_y_alchss_sum(data) ## End(Not run)
Computes the summary score su_y_alcprob_prsum
Alcohol Problem Index (RAPI) [Youth]: Prorated sum [Validation: No more
than 2 missing or declined]
Summarized variables:
su_y_alcprob_001
su_y_alcprob_002
su_y_alcprob_003
su_y_alcprob_004
su_y_alcprob_005
su_y_alcprob_006
su_y_alcprob_007
su_y_alcprob_008
su_y_alcprob_009
su_y_alcprob_010
su_y_alcprob_012
su_y_alcprob_016
su_y_alcprob_017
su_y_alcprob_018
su_y_alcprob_001__l
su_y_alcprob_002__l
su_y_alcprob_003__l
su_y_alcprob_004__l
su_y_alcprob_005__l
su_y_alcprob_006__l
su_y_alcprob_007__l
su_y_alcprob_008__l
su_y_alcprob_009__l
su_y_alcprob_010__l
su_y_alcprob_012__l
su_y_alcprob_016__l
su_y_alcprob_017__l
su_y_alcprob_018__l
Excluded values: none
Validation criterion: maximally 2 items missing
vars_su_y_alcprob compute_su_y_alcprob_prsum( data, name = "su_y_alcprob_prsum", combine = TRUE, max_na = 2 )vars_su_y_alcprob compute_su_y_alcprob_prsum( data, name = "su_y_alcprob_prsum", combine = TRUE, max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_alcprob is a table with pairs of baseline and longitudinal
redcap fields used to compute summary score of su_y_alcprob_prsum and
su_y_alcprob_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__6mo_mean
Alcohol Subject Response and Effects [Youth] (Last 6 months): Mean
[Validation: None missing or declined]
Summarized variables:
su_y_alcsre__6mo_001
su_y_alcsre__6mo_002
su_y_alcsre__6mo_003
su_y_alcsre__6mo_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
vars_su_y_alcsre__6mo compute_su_y_alcsre__6mo_mean( data, name = "su_y_alcsre__6mo_mean", combine = TRUE, max_na = 0 )vars_su_y_alcsre__6mo compute_su_y_alcsre__6mo_mean( data, name = "su_y_alcsre__6mo_mean", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_alcsre__6mo is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__6mo (_mean, _count, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__first5_mean
Alcohol Subject Response and Effects [Youth] (First 5 times ever
drank): Mean [Validation: None missing or declined]
Summarized variables:
su_y_alcsre__first5_001
su_y_alcsre__first5_002
su_y_alcsre__first5_003
su_y_alcsre__first5_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
vars_su_y_alcsre__first5 compute_su_y_alcsre__first5_mean( data, name = "su_y_alcsre__first5_mean", combine = TRUE, max_na = 0 )vars_su_y_alcsre__first5 compute_su_y_alcsre__first5_mean( data, name = "su_y_alcsre__first5_mean", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_alcsre__first5 is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__first5 (_mean, _count, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_alcsre__hvy_mean
Alcohol Subject Response and Effects [Youth] (Heaviest drinking
period): Mean [Validation: None missing or declined]
Summarized variables:
su_y_alcsre__hvy_001
su_y_alcsre__hvy_002
su_y_alcsre__hvy_003
su_y_alcsre__hvy_004
Excluded values: none
Validation criterion: maximally 0 of 4 items missing
vars_su_y_alcsre__hvy compute_su_y_alcsre__hvy_mean( data, name = "su_y_alcsre__hvy_mean", combine = TRUE, max_na = 0 )vars_su_y_alcsre__hvy compute_su_y_alcsre__hvy_mean( data, name = "su_y_alcsre__hvy_mean", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_alcsre__hvy is a character vector of
all column names used to compute summary scores of
compute_su_y_alcsre__hvy (_mean, _count, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__coffee_sum
Caffeine Use Questionnaire [Youth] (Coffee): Sum [Validation: None]
Summarized variables:
su_y_caff__coffee_001
su_y_caff__coffee_001__01__01
su_y_caff__coffee_001__01__02
su_y_caff__coffee_001__01__03
su_y_caff__coffee_001__02__01
su_y_caff__coffee_001__02__02
su_y_caff__coffee_001__02__03
su_y_caff__coffee_001__03__01
su_y_caff__coffee_001__03__02
su_y_caff__coffee_001__03__03
su_y_caff__coffee_001__04__01
su_y_caff__coffee_001__04__02
su_y_caff__coffee_001__04__03
su_y_caff__coffee_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__coffee compute_su_y_caff__coffee_sum( data, name = "su_y_caff__coffee_sum", combine = TRUE )vars_su_y_caff__coffee compute_su_y_caff__coffee_sum( data, name = "su_y_caff__coffee_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__coffee is a character vector of all column names used
to compute compute_su_y_caff__coffee_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__energy_sum
Caffeine Use Questionnaire [Youth] (Energy): Sum [Validation: None]
Summarized variables:
su_y_caff__energy_001
su_y_caff__energy_001__l
su_y_caff__energy__shot_001__01
su_y_caff__energy__shot_001__02
su_y_caff__energy__drink_001__01__01
su_y_caff__energy__drink_001__01__02
su_y_caff__energy__drink_001__01__03
su_y_caff__energy__drink_001__02__01
su_y_caff__energy__drink_001__02__02
su_y_caff__energy__drink_001__02__03
su_y_caff__energy__drink_001__03__01
su_y_caff__energy__drink_001__03__02
su_y_caff__energy__drink_001__03__03
su_y_caff__energy__drink_001__04__01
su_y_caff__energy__drink_001__04__02
su_y_caff__energy__drink_001__04__03
Excluded values: none
Validation criterion: none
vars_su_y_caff__energy compute_su_y_caff__energy_sum( data, name = "su_y_caff__energy_sum", combine = TRUE )vars_su_y_caff__energy compute_su_y_caff__energy_sum( data, name = "su_y_caff__energy_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__energy is a character vector of all column names used
to compute compute_su_y_caff__energy_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__energy__drink_sum
Caffeine Use Questionnaire [Youth] (Energy drink):
Sum [Validation: None]
Summarized variables:
su_y_caff__energy__drink_001__01__01
su_y_caff__energy__drink_001__01__02
su_y_caff__energy__drink_001__01__03
su_y_caff__energy__drink_001__02__01
su_y_caff__energy__drink_001__02__02
su_y_caff__energy__drink_001__02__03
su_y_caff__energy__drink_001__03__01
su_y_caff__energy__drink_001__03__02
su_y_caff__energy__drink_001__03__03
su_y_caff__energy__drink_001__04__01
su_y_caff__energy__drink_001__04__02
su_y_caff__energy__drink_001__04__03
Excluded values: none
Validation criterion: none
vars_su_y_caff__energy__drink compute_su_y_caff__energy__drink_sum( data, name = "su_y_caff__energy__drink_sum", combine = TRUE )vars_su_y_caff__energy__drink compute_su_y_caff__energy__drink_sum( data, name = "su_y_caff__energy__drink_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__energy__drink is a character vector
of all column names used to compute compute_su_y_caff__energy__drink_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__energy__shot_sum
Caffeine Use Questionnaire [Youth] (Energy shot): Sum [Validation: None]
Summarized variables:
su_y_caff__energy__shot_001__01
su_y_caff__energy__shot_001__02
Excluded values: none
Validation criterion: none
vars_su_y_caff__energy__shot compute_su_y_caff__energy__shot_sum( data, name = "su_y_caff__energy__shot_sum", combine = TRUE )vars_su_y_caff__energy__shot compute_su_y_caff__energy__shot_sum( data, name = "su_y_caff__energy__shot_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__energy__shot is a character vector of all column
names used to compute compute_su_y_caff__energy__shot_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__espres_sum
Caffeine Use Questionnaire [Youth] (Espresso): Sum [Validation: None]
Summarized variables:
su_y_caff__espres_001
su_y_caff__espres_001__01
su_y_caff__espres_001__02
su_y_caff__espres_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__espres compute_su_y_caff__espres_sum( data, name = "su_y_caff__espres_sum", combine = TRUE )vars_su_y_caff__espres compute_su_y_caff__espres_sum( data, name = "su_y_caff__espres_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__espres is a character vector of all column names used
to compute compute_su_y_caff__espres_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__oth_sum
Caffeine Use Questionnaire [Youth] (Other): Sum [Validation: None]
Summarized variables:
su_y_caff__oth_001__01
su_y_caff__oth_001__02
su_y_caff__oth_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__oth compute_su_y_caff__oth_sum(data, name = "su_y_caff__oth_sum", combine = TRUE)vars_su_y_caff__oth compute_su_y_caff__oth_sum(data, name = "su_y_caff__oth_sum", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__oth is a character vector of all column names used
to compute compute_su_y_caff__oth_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__soda_sum
Caffeine Use Questionnaire [Youth] (Soda) : Sum [Validation: None]
Summarized variables:
su_y_caff__soda_001
su_y_caff__soda_001__01__01
su_y_caff__soda_001__01__02
su_y_caff__soda_001__01__03
su_y_caff__soda_001__02__01
su_y_caff__soda_001__02__02
su_y_caff__soda_001__02__03
su_y_caff__soda_001__03__01
su_y_caff__soda_001__03__02
su_y_caff__soda_001__03__03
su_y_caff__soda_001__04__01
su_y_caff__soda_001__04__02
su_y_caff__soda_001__04__03
su_y_caff__soda_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__soda compute_su_y_caff__soda_sum(data, name = "su_y_caff__soda_sum", combine = TRUE)vars_su_y_caff__soda compute_su_y_caff__soda_sum(data, name = "su_y_caff__soda_sum", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__soda is a character vector of all column names used
to compute compute_su_y_caff__soda_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__suppl_sum
Caffeine Use Questionnaire [Youth] (Caffeine supplements):
Sum [Validation: None]
Summarized variables:
su_y_caff__suppl_001__01__01
su_y_caff__suppl_001__01__02
su_y_caff__suppl_001__02__01
su_y_caff__suppl_001__02__02
su_y_caff__suppl_001__03__01
su_y_caff__suppl_001__03__02
su_y_caff__suppl_001__04__01
su_y_caff__suppl_001__04__02
su_y_caff__suppl_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__suppl compute_su_y_caff__suppl_sum( data, name = "su_y_caff__suppl_sum", combine = TRUE )vars_su_y_caff__suppl compute_su_y_caff__suppl_sum( data, name = "su_y_caff__suppl_sum", combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__suppl is a character vector of all column names used
to compute compute_su_y_caff__suppl_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_caff__tea_sum
Caffeine Use Questionnaire [Youth] (Tea) : Sum [Validation: None]
Summarized variables:
su_y_caff__tea_001
su_y_caff__tea_001__01__01
su_y_caff__tea_001__01__02
su_y_caff__tea_001__01__03
su_y_caff__tea_001__02__01
su_y_caff__tea_001__02__02
su_y_caff__tea_001__02__03
su_y_caff__tea_001__03__01
su_y_caff__tea_001__03__02
su_y_caff__tea_001__03__03
su_y_caff__tea_001__04__01
su_y_caff__tea_001__04__02
su_y_caff__tea_001__04__03
su_y_caff__tea_001__l
Excluded values: none
Validation criterion: none
vars_su_y_caff__tea compute_su_y_caff__tea_sum(data, name = "su_y_caff__tea_sum", combine = TRUE)vars_su_y_caff__tea compute_su_y_caff__tea_sum(data, name = "su_y_caff__tea_sum", combine = TRUE)
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
vars_su_y_caff__tea is a character vector of all column names used
to compute compute_su_y_caff__tea_sum.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_cigexp__neg_prsum
Cigarette Expectancies (ASCQ) [Youth] (Strength of negative
expectancies): Prorated sum [Validation: No more than 0
missing or declined]
Note: all 0s are changed to NAs prior to calculating pro-rated sum
Summarized variables:
su_y_cigexp__neg_001
su_y_cigexp__neg_002
Excluded values:
0
Validation criterion: maximally 0 of 2 items missing
vars_su_y_cigexp__neg compute_su_y_cigexp__neg_prsum( data, name = "su_y_cigexp__neg_prsum", combine = TRUE, exclude = c("0"), max_na = 0 )vars_su_y_cigexp__neg compute_su_y_cigexp__neg_prsum( data, name = "su_y_cigexp__neg_prsum", combine = TRUE, exclude = c("0"), max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_cigexp__neg is a character vector of all column names
used to compute summary score of su_y_cigexp__neg_prsum and
su_y_cigexp__neg_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_cigexp__pos_prsum
Cigarette Expectancies (ASCQ) [Youth] (Strength of positive
expectancies): Prorated sum
Note: all 0s are changed to NAs prior to calculating pro-rated sum
Summarized variables:
su_y_cigexp__pos_001
su_y_cigexp__pos_002
su_y_cigexp__pos_003
su_y_cigexp__pos_004
Excluded values:
0
Validation criterion: maximally 2 of 4 items missing
vars_su_y_cigexp__pos compute_su_y_cigexp__pos_prsum( data, name = "su_y_cigexp__pos_prsum", combine = TRUE, exclude = c("0"), max_na = 2 )vars_su_y_cigexp__pos compute_su_y_cigexp__pos_prsum( data, name = "su_y_cigexp__pos_prsum", combine = TRUE, exclude = c("0"), max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
exclude |
character vector. Values to be excluded from the summary score calculation. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_cigexp__pos is a character vector of all column names
used to compute summary score of su_y_cigexp__pos_prsum and
su_y_cigexp__pos_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_drgprob_prsum
Drug Problem Index (DAPI) [Youth]: Prorated sum [Validation: No more
than 3 missing or declined]
Summarized variables:
su_y_drgprob_001
su_y_drgprob_002
su_y_drgprob_003
su_y_drgprob_004
su_y_drgprob_005
su_y_drgprob_006
su_y_drgprob_007
su_y_drgprob_008
su_y_drgprob_009
su_y_drgprob_010
su_y_drgprob_012
su_y_drgprob_013
su_y_drgprob_014
su_y_drgprob_015
su_y_drgprob_016
su_y_drgprob_017
su_y_drgprob_018
Excluded values: none
Validation criterion: maximally 3 items missing
vars_su_y_drgprob compute_su_y_drgprob_prsum( data, name = "su_y_drgprob_prsum", combine = TRUE, max_na = 3 )vars_su_y_drgprob compute_su_y_drgprob_prsum( data, name = "su_y_drgprob_prsum", combine = TRUE, max_na = 3 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_drgprob is a character vector of all column names
used to compute summary score of su_y_drgprob_prsum and
su_y_drgprob_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_ksads__aud__past__sx_mean
KSADS - Alcohol Use Disorder [Youth] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_y_ksads__aud__actvdecr__past_sx
su_y_ksads__aud__crave__past_sx
su_y_ksads__aud__dwi__past_sx
su_y_ksads__aud__failrespons__past_sx
su_y_ksads__aud__haz__past_sx
su_y_ksads__aud__negimpct__interprs__past_sx
su_y_ksads__aud__overuse__past_sx
su_y_ksads__aud__prob__phys__past_sx
su_y_ksads__aud__prob__psych__past_sx
su_y_ksads__aud__reduce__dsr__past_sx
su_y_ksads__aud__reduce__unsucces__past_sx
su_y_ksads__aud__time__past_sx
su_y_ksads__aud__tol__past_sx
su_y_ksads__aud__withdr__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_y_ksads__aud__past__sx compute_su_y_ksads__aud__past__sx_mean( data, name = "su_y_ksads__aud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_y_ksads__aud__past__sx compute_su_y_ksads__aud__past__sx_mean( data, name = "su_y_ksads__aud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__aud__past__sx is a character vector
of all column names used to compute summary score of
su_y_ksads__aud__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__aud__pres__sx_mean
KSADS - Alcohol Use Disorder [Youth] (Symptom - Present): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_y_ksads__aud__actvdecr__pres_sx
su_y_ksads__aud__crave__pres_sx
su_y_ksads__aud__dwi__pres_sx
su_y_ksads__aud__failrespons__pres_sx
su_y_ksads__aud__haz__pres_sx
su_y_ksads__aud__negimpct__interprs__pres_sx
su_y_ksads__aud__overuse__pres_sx
su_y_ksads__aud__prob__phys__pres_sx
su_y_ksads__aud__prob__psych__pres_sx
su_y_ksads__aud__reduce__dsr__pres_sx
su_y_ksads__aud__reduce__unsucces__pres_sx
su_y_ksads__aud__time__pres_sx
su_y_ksads__aud__tol__pres_sx
su_y_ksads__aud__withdr__pres_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_y_ksads__aud__pres__sx compute_su_y_ksads__aud__pres__sx_mean( data, name = "su_y_ksads__aud__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_y_ksads__aud__pres__sx compute_su_y_ksads__aud__pres__sx_mean( data, name = "su_y_ksads__aud__pres__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__aud__pres__sx is a character vector
of all column names used to compute summary score of
su_y_ksads__aud__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__coc__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Cocaine - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__coc__past_sx
su_y_ksads__dud__crave__coc__past_sx
su_y_ksads__dud__dwi__coc__past_sx
su_y_ksads__dud__failrespons__coc__past_sx
su_y_ksads__dud__haz__coc__past_sx
su_y_ksads__dud__negimpct__interprs__coc__past_sx
su_y_ksads__dud__negimpct__obl__coc__past_sx
su_y_ksads__dud__overuse__coc__past_sx
su_y_ksads__dud__prob__phys__coc__past_sx
su_y_ksads__dud__prob__psych__coc__past_sx
su_y_ksads__dud__reduce__dsr__coc__past_sx
su_y_ksads__dud__reduce__unsucces__coc__past_sx
su_y_ksads__dud__time__coc__past_sx
su_y_ksads__dud__tol__coc__past_sx
su_y_ksads__dud__withdr__coc__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__coc__past__sx_mean compute_su_y_ksads__dud__coc__past__sx_mean( data, name = "su_y_ksads__dud__coc__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__coc__past__sx_mean compute_su_y_ksads__dud__coc__past__sx_mean( data, name = "su_y_ksads__dud__coc__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__coc__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__coc__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__coc__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Cocaine - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__coc__pres_sx
su_y_ksads__dud__crave__coc__pres_sx
su_y_ksads__dud__dwi__coc__pres_sx
su_y_ksads__dud__failrespons__coc__pres_sx
su_y_ksads__dud__haz__coc__pres_sx
su_y_ksads__dud__negimpct__interprs__coc__pres_sx
su_y_ksads__dud__negimpct__obl__coc__pres_sx
su_y_ksads__dud__overuse__coc__pres_sx
su_y_ksads__dud__prob__phys__coc__pres_sx
su_y_ksads__dud__prob__psych__coc__pres_sx
su_y_ksads__dud__reduce__dsr__coc__pres_sx
su_y_ksads__dud__reduce__unsucces__coc__pres_sx
su_y_ksads__dud__time__coc__pres_sx
su_y_ksads__dud__tol__coc__pres_sx
su_y_ksads__dud__withdr__coc__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__coc__pres__sx_mean compute_su_y_ksads__dud__coc__pres__sx_mean( data, name = "su_y_ksads__dud__coc__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__coc__pres__sx_mean compute_su_y_ksads__dud__coc__pres__sx_mean( data, name = "su_y_ksads__dud__coc__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__coc__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__coc__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__hall__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Hallucinogen - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__hall__past_sx
su_y_ksads__dud__crave__hall__past_sx
su_y_ksads__dud__dwi__hall__past_sx
su_y_ksads__dud__failrespons__hall__past_sx
su_y_ksads__dud__haz__hall__past_sx
su_y_ksads__dud__negimpct__interprs__hall__past_sx
su_y_ksads__dud__negimpct__obl__hall__past_sx
su_y_ksads__dud__overuse__hall__past_sx
su_y_ksads__dud__prob__phys__hall__past_sx
su_y_ksads__dud__prob__psych__hall__past_sx
su_y_ksads__dud__reduce__dsr__hall__past_sx
su_y_ksads__dud__reduce__unsucces__hall__past_sx
su_y_ksads__dud__time__hall__past_sx
su_y_ksads__dud__tol__hall__past_sx
su_y_ksads__dud__withdr__hall__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__hall__past__sx_mean compute_su_y_ksads__dud__hall__past__sx_mean( data, name = "su_y_ksads__dud__hall__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__hall__past__sx_mean compute_su_y_ksads__dud__hall__past__sx_mean( data, name = "su_y_ksads__dud__hall__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__hall__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__hall__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__hall__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Hallucinogen - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__hall__pres_sx
su_y_ksads__dud__crave__hall__pres_sx
su_y_ksads__dud__dwi__hall__pres_sx
su_y_ksads__dud__failrespons__hall__pres_sx
su_y_ksads__dud__haz__hall__pres_sx
su_y_ksads__dud__negimpct__interprs__hall__pres_sx
su_y_ksads__dud__negimpct__obl__hall__pres_sx
su_y_ksads__dud__overuse__hall__pres_sx
su_y_ksads__dud__prob__phys__hall__pres_sx
su_y_ksads__dud__prob__psych__hall__pres_sx
su_y_ksads__dud__reduce__dsr__hall__pres_sx
su_y_ksads__dud__reduce__unsucces__hall__pres_sx
su_y_ksads__dud__time__hall__pres_sx
su_y_ksads__dud__tol__hall__pres_sx
su_y_ksads__dud__withdr__hall__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__hall__pres__sx_mean compute_su_y_ksads__dud__hall__pres__sx_mean( data, name = "su_y_ksads__dud__hall__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__hall__pres__sx_mean compute_su_y_ksads__dud__hall__pres__sx_mean( data, name = "su_y_ksads__dud__hall__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__hall__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__hall__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__mj__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Cannabis - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__mj__past_sx
su_y_ksads__dud__crave__mj__past_sx
su_y_ksads__dud__dwi__mj__past_sx
su_y_ksads__dud__failrespons__mj__past_sx
su_y_ksads__dud__haz__mj__past_sx
su_y_ksads__dud__negimpct__interprs__mj__past_sx
su_y_ksads__dud__negimpct__obl__mj__past_sx
su_y_ksads__dud__overuse__mj__past_sx
su_y_ksads__dud__prob__phys__mj__past_sx
su_y_ksads__dud__prob__psych__mj__past_sx
su_y_ksads__dud__reduce__dsr__mj__past_sx
su_y_ksads__dud__reduce__unsucces__mj__past_sx
su_y_ksads__dud__time__mj__past_sx
su_y_ksads__dud__tol__mj__past_sx
su_y_ksads__dud__withdr__mj__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__mj__past__sx_mean compute_su_y_ksads__dud__mj__past__sx_mean( data, name = "su_y_ksads__dud__mj__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__mj__past__sx_mean compute_su_y_ksads__dud__mj__past__sx_mean( data, name = "su_y_ksads__dud__mj__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__mj__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__mj__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__mj__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Cannabis - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__mj__pres_sx
su_y_ksads__dud__crave__mj__pres_sx
su_y_ksads__dud__dwi__mj__pres_sx
su_y_ksads__dud__failrespons__mj__pres_sx
su_y_ksads__dud__haz__mj__pres_sx
su_y_ksads__dud__negimpct__interprs__mj__pres_sx
su_y_ksads__dud__negimpct__obl__mj__pres_sx
su_y_ksads__dud__overuse__mj__pres_sx
su_y_ksads__dud__prob__phys__mj__pres_sx
su_y_ksads__dud__prob__psych__mj__pres_sx
su_y_ksads__dud__reduce__dsr__mj__pres_sx
su_y_ksads__dud__reduce__unsucces__mj__pres_sx
su_y_ksads__dud__time__mj__pres_sx
su_y_ksads__dud__tol__mj__pres_sx
su_y_ksads__dud__withdr__mj__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__mj__pres__sx_mean compute_su_y_ksads__dud__mj__pres__sx_mean( data, name = "su_y_ksads__dud__mj__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__mj__pres__sx_mean compute_su_y_ksads__dud__mj__pres__sx_mean( data, name = "su_y_ksads__dud__mj__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__mj__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__mj__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__nic__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Tobacco - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__nic__past_sx
su_y_ksads__dud__crave__nic__past_sx
su_y_ksads__dud__dwi__nic__past_sx
su_y_ksads__dud__failrespons__nic__past_sx
su_y_ksads__dud__haz__nic__past_sx
su_y_ksads__dud__negimpct__interprs__nic__past_sx
su_y_ksads__dud__negimpct__obl__nic__past_sx
su_y_ksads__dud__overuse__nic__past_sx
su_y_ksads__dud__prob__phys__nic__past_sx
su_y_ksads__dud__prob__psych__nic__past_sx
su_y_ksads__dud__reduce__dsr__nic__past_sx
su_y_ksads__dud__reduce__unsucces__nic__past_sx
su_y_ksads__dud__time__nic__past_sx
su_y_ksads__dud__tol__nic__past_sx
su_y_ksads__dud__withdr__nic__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__nic__past__sx_mean compute_su_y_ksads__dud__nic__past__sx_mean( data, name = "su_y_ksads__dud__nic__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__nic__past__sx_mean compute_su_y_ksads__dud__nic__past__sx_mean( data, name = "su_y_ksads__dud__nic__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__nic__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__nic__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__nic__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Tobacco - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__nic__pres_sx
su_y_ksads__dud__crave__nic__pres_sx
su_y_ksads__dud__dwi__nic__pres_sx
su_y_ksads__dud__failrespons__nic__pres_sx
su_y_ksads__dud__haz__nic__pres_sx
su_y_ksads__dud__negimpct__interprs__nic__pres_sx
su_y_ksads__dud__negimpct__obl__nic__pres_sx
su_y_ksads__dud__overuse__nic__pres_sx
su_y_ksads__dud__prob__phys__nic__pres_sx
su_y_ksads__dud__prob__psych__nic__pres_sx
su_y_ksads__dud__reduce__dsr__nic__pres_sx
su_y_ksads__dud__reduce__unsucces__nic__pres_sx
su_y_ksads__dud__time__nic__pres_sx
su_y_ksads__dud__tol__nic__pres_sx
su_y_ksads__dud__withdr__nic__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__nic__pres__sx_mean compute_su_y_ksads__dud__nic__pres__sx_mean( data, name = "su_y_ksads__dud__nic__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__nic__pres__sx_mean compute_su_y_ksads__dud__nic__pres__sx_mean( data, name = "su_y_ksads__dud__nic__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__nic__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__nic__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__opi__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Opiod - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__opi__past_sx
su_y_ksads__dud__crave__opi__past_sx
su_y_ksads__dud__dwi__opi__past_sx
su_y_ksads__dud__failrespons__opi__past_sx
su_y_ksads__dud__haz__opi__past_sx
su_y_ksads__dud__negimpct__interprs__opi__past_sx
su_y_ksads__dud__negimpct__obl__opi__past_sx
su_y_ksads__dud__overuse__opi__past_sx
su_y_ksads__dud__prob__phys__opi__past_sx
su_y_ksads__dud__prob__psych__opi__past_sx
su_y_ksads__dud__reduce__dsr__opi__past_sx
su_y_ksads__dud__reduce__unsucces__opi__past_sx
su_y_ksads__dud__time__opi__past_sx
su_y_ksads__dud__tol__opi__past_sx
su_y_ksads__dud__withdr__opi__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__opi__past__sx_mean compute_su_y_ksads__dud__opi__past__sx_mean( data, name = "su_y_ksads__dud__opi__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__opi__past__sx_mean compute_su_y_ksads__dud__opi__past__sx_mean( data, name = "su_y_ksads__dud__opi__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__opi__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__opi__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__opi__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Opiod - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__opi__pres_sx
su_y_ksads__dud__crave__opi__pres_sx
su_y_ksads__dud__dwi__opi__pres_sx
su_y_ksads__dud__failrespons__opi__pres_sx
su_y_ksads__dud__haz__opi__pres_sx
su_y_ksads__dud__negimpct__interprs__opi__pres_sx
su_y_ksads__dud__negimpct__obl__opi__pres_sx
su_y_ksads__dud__overuse__opi__pres_sx
su_y_ksads__dud__prob__phys__opi__pres_sx
su_y_ksads__dud__prob__psych__opi__pres_sx
su_y_ksads__dud__reduce__dsr__opi__pres_sx
su_y_ksads__dud__reduce__unsucces__opi__pres_sx
su_y_ksads__dud__time__opi__pres_sx
su_y_ksads__dud__tol__opi__pres_sx
su_y_ksads__dud__withdr__opi__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__opi__pres__sx_mean compute_su_y_ksads__dud__opi__pres__sx_mean( data, name = "su_y_ksads__dud__opi__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__opi__pres__sx_mean compute_su_y_ksads__dud__opi__pres__sx_mean( data, name = "su_y_ksads__dud__opi__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__opi__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__opi__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__othdrg__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Other drugs - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__othdrg__past_sx
su_y_ksads__dud__crave__othdrg__past_sx
su_y_ksads__dud__dwi__othdrg__past_sx
su_y_ksads__dud__failrespons__othdrg__past_sx
su_y_ksads__dud__haz__othdrg__past_sx
su_y_ksads__dud__negimpct__interprs__othdrg__past_sx
su_y_ksads__dud__negimpct__obl__othdrg__past_sx
su_y_ksads__dud__overuse__othdrg__past_sx
su_y_ksads__dud__prob__phys__othdrg__past_sx
su_y_ksads__dud__prob__psych__othdrg__past_sx
su_y_ksads__dud__reduce__dsr__othdrg__past_sx
su_y_ksads__dud__reduce__unsucces__othdrg__past_sx
su_y_ksads__dud__time__othdrg__past_sx
su_y_ksads__dud__tol__othdrg__past_sx
su_y_ksads__dud__withdr__othdrg__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__othdrg__past__sx_mean compute_su_y_ksads__dud__othdrg__past__sx_mean( data, name = "su_y_ksads__dud__othdrg__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__othdrg__past__sx_mean compute_su_y_ksads__dud__othdrg__past__sx_mean( data, name = "su_y_ksads__dud__othdrg__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__othdrg__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__othdrg__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__othdrg__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Other drugs - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__othdrg__pres_sx
su_y_ksads__dud__crave__othdrg__pres_sx
su_y_ksads__dud__dwi__othdrg__pres_sx
su_y_ksads__dud__failrespons__othdrg__pres_sx
su_y_ksads__dud__haz__othdrg__pres_sx
su_y_ksads__dud__negimpct__interprs__othdrg__pres_sx
su_y_ksads__dud__negimpct__obl__othdrg__pres_sx
su_y_ksads__dud__overuse__othdrg__pres_sx
su_y_ksads__dud__prob__phys__othdrg__pres_sx
su_y_ksads__dud__prob__psych__othdrg__pres_sx
su_y_ksads__dud__reduce__dsr__othdrg__pres_sx
su_y_ksads__dud__reduce__unsucces__othdrg__pres_sx
su_y_ksads__dud__time__othdrg__pres_sx
su_y_ksads__dud__tol__othdrg__pres_sx
su_y_ksads__dud__withdr__othdrg__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__othdrg__pres__sx_mean compute_su_y_ksads__dud__othdrg__pres__sx_mean( data, name = "su_y_ksads__dud__othdrg__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__othdrg__pres__sx_mean compute_su_y_ksads__dud__othdrg__pres__sx_mean( data, name = "su_y_ksads__dud__othdrg__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__othdrg__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__othdrg__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom - Past): Mean
[Validation: No more than 2 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__past_sx
su_y_ksads__dud__crave__past_sx
su_y_ksads__dud__dwi__past_sx
su_y_ksads__dud__failrespons__past_sx
su_y_ksads__dud__haz__past_sx
su_y_ksads__dud__negimpct__interprs__past_sx
su_y_ksads__dud__negimpct__obl__past_sx
su_y_ksads__dud__overuse__past_sx
su_y_ksads__dud__prob__phys__past_sx
su_y_ksads__dud__prob__psych__past_sx
su_y_ksads__dud__reduce__dsr__past_sx
su_y_ksads__dud__reduce__unsucces__past_sx
su_y_ksads__dud__tol__past_sx
su_y_ksads__dud__withdr__past_sx
Excluded values:
555
Validation criterion: maximally 2 of 14 items missing
vars_su_y_ksads__dud__past__sx_mean compute_su_y_ksads__dud__past__sx_mean( data, name = "su_y_ksads__dud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__past__sx_mean compute_su_y_ksads__dud__past__sx_mean( data, name = "su_y_ksads__dud__past__sx_mean", max_na = 2, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__pcp__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: PCP - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__pcp__past_sx
su_y_ksads__dud__crave__pcp__past_sx
su_y_ksads__dud__dwi__pcp__past_sx
su_y_ksads__dud__failrespons__pcp__past_sx
su_y_ksads__dud__haz__pcp__past_sx
su_y_ksads__dud__negimpct__interprs__pcp__past_sx
su_y_ksads__dud__negimpct__obl__pcp__past_sx
su_y_ksads__dud__overuse__pcp__past_sx
su_y_ksads__dud__prob__phys__pcp__past_sx
su_y_ksads__dud__prob__psych__pcp__past_sx
su_y_ksads__dud__reduce__dsr__pcp__past_sx
su_y_ksads__dud__reduce__unsucces__pcp__past_sx
su_y_ksads__dud__time__pcp__past_sx
su_y_ksads__dud__tol__pcp__past_sx
su_y_ksads__dud__withdr__pcp__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__pcp__past__sx_mean compute_su_y_ksads__dud__pcp__past__sx_mean( data, name = "su_y_ksads__dud__pcp__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__pcp__past__sx_mean compute_su_y_ksads__dud__pcp__past__sx_mean( data, name = "su_y_ksads__dud__pcp__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__pcp__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__pcp__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__pcp__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: PCP - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__pcp__pres_sx
su_y_ksads__dud__crave__pcp__pres_sx
su_y_ksads__dud__dwi__pcp__pres_sx
su_y_ksads__dud__failrespons__pcp__pres_sx
su_y_ksads__dud__haz__pcp__pres_sx
su_y_ksads__dud__negimpct__interprs__pcp__pres_sx
su_y_ksads__dud__negimpct__obl__pcp__pres_sx
su_y_ksads__dud__overuse__pcp__pres_sx
su_y_ksads__dud__prob__phys__pcp__pres_sx
su_y_ksads__dud__prob__psych__pcp__pres_sx
su_y_ksads__dud__reduce__dsr__pcp__pres_sx
su_y_ksads__dud__reduce__unsucces__pcp__pres_sx
su_y_ksads__dud__time__pcp__pres_sx
su_y_ksads__dud__tol__pcp__pres_sx
su_y_ksads__dud__withdr__pcp__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__pcp__pres__sx_mean compute_su_y_ksads__dud__pcp__pres__sx_mean( data, name = "su_y_ksads__dud__pcp__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__pcp__pres__sx_mean compute_su_y_ksads__dud__pcp__pres__sx_mean( data, name = "su_y_ksads__dud__pcp__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__pcp__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__pcp__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__pres_sx
su_y_ksads__dud__crave__pres_sx
su_y_ksads__dud__dwi__pres_sx
su_y_ksads__dud__failrespons__pres_sx
su_y_ksads__dud__haz__pres_sx
su_y_ksads__dud__negimpct__interprs__pres_sx
su_y_ksads__dud__negimpct__obl__pres_sx
su_y_ksads__dud__overuse__pres_sx
su_y_ksads__dud__prob__phys__pres_sx
su_y_ksads__dud__prob__psych__pres_sx
su_y_ksads__dud__reduce__dsr__pres_sx
su_y_ksads__dud__reduce__unsucces__pres_sx
su_y_ksads__dud__time__pres_sx
su_y_ksads__dud__tol__pres_sx
su_y_ksads__dud__withdr__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__pres__sx_mean compute_su_y_ksads__dud__pres__sx_mean( data, name = "su_y_ksads__dud__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__pres__sx_mean compute_su_y_ksads__dud__pres__sx_mean( data, name = "su_y_ksads__dud__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__sed__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Sedatives - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__sed__past_sx
su_y_ksads__dud__crave__sed__past_sx
su_y_ksads__dud__dwi__sed__past_sx
su_y_ksads__dud__failrespons__sed__past_sx
su_y_ksads__dud__haz__sed__past_sx
su_y_ksads__dud__negimpct__interprs__sed__past_sx
su_y_ksads__dud__negimpct__obl__sed__past_sx
su_y_ksads__dud__overuse__sed__past_sx
su_y_ksads__dud__prob__phys__sed__past_sx
su_y_ksads__dud__prob__psych__sed__past_sx
su_y_ksads__dud__reduce__dsr__sed__past_sx
su_y_ksads__dud__reduce__unsucces__sed__past_sx
su_y_ksads__dud__time__sed__past_sx
su_y_ksads__dud__tol__sed__past_sx
su_y_ksads__dud__withdr__sed__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__sed__past__sx_mean compute_su_y_ksads__dud__sed__past__sx_mean( data, name = "su_y_ksads__dud__sed__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__sed__past__sx_mean compute_su_y_ksads__dud__sed__past__sx_mean( data, name = "su_y_ksads__dud__sed__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__sed__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__sed__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__sed__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Sedatives - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__sed__pres_sx
su_y_ksads__dud__crave__sed__pres_sx
su_y_ksads__dud__dwi__sed__pres_sx
su_y_ksads__dud__failrespons__sed__pres_sx
su_y_ksads__dud__haz__sed__pres_sx
su_y_ksads__dud__negimpct__interprs__sed__pres_sx
su_y_ksads__dud__negimpct__obl__sed__pres_sx
su_y_ksads__dud__overuse__sed__pres_sx
su_y_ksads__dud__prob__phys__sed__pres_sx
su_y_ksads__dud__prob__psych__sed__pres_sx
su_y_ksads__dud__reduce__dsr__sed__pres_sx
su_y_ksads__dud__reduce__unsucces__sed__pres_sx
su_y_ksads__dud__time__sed__pres_sx
su_y_ksads__dud__tol__sed__pres_sx
su_y_ksads__dud__withdr__sed__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__sed__pres__sx_mean compute_su_y_ksads__dud__sed__pres__sx_mean( data, name = "su_y_ksads__dud__sed__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__sed__pres__sx_mean compute_su_y_ksads__dud__sed__pres__sx_mean( data, name = "su_y_ksads__dud__sed__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__sed__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__sed__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__solv__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Solvent - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__solv__past_sx
su_y_ksads__dud__crave__solv__past_sx
su_y_ksads__dud__dwi__solv__past_sx
su_y_ksads__dud__failrespons__solv__past_sx
su_y_ksads__dud__haz__solv__past_sx
su_y_ksads__dud__negimpct__interprs__solv__past_sx
su_y_ksads__dud__negimpct__obl__solv__past_sx
su_y_ksads__dud__overuse__solv__past_sx
su_y_ksads__dud__prob__phys__solv__past_sx
su_y_ksads__dud__prob__psych__solv__past_sx
su_y_ksads__dud__reduce__dsr__solv__past_sx
su_y_ksads__dud__reduce__unsucces__solv__past_sx
su_y_ksads__dud__time__solv__past_sx
su_y_ksads__dud__tol__solv__past_sx
su_y_ksads__dud__withdr__solv__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__solv__past__sx_mean compute_su_y_ksads__dud__solv__past__sx_mean( data, name = "su_y_ksads__dud__solv__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__solv__past__sx_mean compute_su_y_ksads__dud__solv__past__sx_mean( data, name = "su_y_ksads__dud__solv__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__solv__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__solv__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__solv__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Solvent - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__solv__pres_sx
su_y_ksads__dud__crave__solv__pres_sx
su_y_ksads__dud__dwi__solv__pres_sx
su_y_ksads__dud__failrespons__solv__pres_sx
su_y_ksads__dud__haz__solv__pres_sx
su_y_ksads__dud__negimpct__interprs__solv__pres_sx
su_y_ksads__dud__negimpct__obl__solv__pres_sx
su_y_ksads__dud__overuse__solv__pres_sx
su_y_ksads__dud__prob__phys__solv__pres_sx
su_y_ksads__dud__prob__psych__solv__pres_sx
su_y_ksads__dud__reduce__dsr__solv__pres_sx
su_y_ksads__dud__reduce__unsucces__solv__pres_sx
su_y_ksads__dud__time__solv__pres_sx
su_y_ksads__dud__tol__solv__pres_sx
su_y_ksads__dud__withdr__solv__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__solv__pres__sx_mean compute_su_y_ksads__dud__solv__pres__sx_mean( data, name = "su_y_ksads__dud__solv__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__solv__pres__sx_mean compute_su_y_ksads__dud__solv__pres__sx_mean( data, name = "su_y_ksads__dud__solv__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__solv__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__solv__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__stim__past__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Stimulants - Past): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__stim__past_sx
su_y_ksads__dud__crave__stim__past_sx
su_y_ksads__dud__dwi__stim__past_sx
su_y_ksads__dud__failrespons__stim__past_sx
su_y_ksads__dud__haz__stim__past_sx
su_y_ksads__dud__negimpct__interprs__stim__past_sx
su_y_ksads__dud__negimpct__obl__stim__past_sx
su_y_ksads__dud__overuse__stim__past_sx
su_y_ksads__dud__prob__phys__stim__past_sx
su_y_ksads__dud__prob__psych__stim__past_sx
su_y_ksads__dud__reduce__dsr__stim__past_sx
su_y_ksads__dud__reduce__unsucces__stim__past_sx
su_y_ksads__dud__time__stim__past_sx
su_y_ksads__dud__tol__stim__past_sx
su_y_ksads__dud__withdr__stim__past_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__stim__past__sx_mean compute_su_y_ksads__dud__stim__past__sx_mean( data, name = "su_y_ksads__dud__stim__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__stim__past__sx_mean compute_su_y_ksads__dud__stim__past__sx_mean( data, name = "su_y_ksads__dud__stim__past__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__stim__past__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__stim__past__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_ksads__dud__stim__pres__sx_mean
KSADS - Drug Use Disorders [Youth] (Symptom: Stimulants - Present): Mean
[Validation: No more than 3 missing or declined]
Summarized variables:
su_y_ksads__dud__actvdecr__stim__pres_sx
su_y_ksads__dud__crave__stim__pres_sx
su_y_ksads__dud__dwi__stim__pres_sx
su_y_ksads__dud__failrespons__stim__pres_sx
su_y_ksads__dud__haz__stim__pres_sx
su_y_ksads__dud__negimpct__interprs__stim__pres_sx
su_y_ksads__dud__negimpct__obl__stim__pres_sx
su_y_ksads__dud__overuse__stim__pres_sx
su_y_ksads__dud__prob__phys__stim__pres_sx
su_y_ksads__dud__prob__psych__stim__pres_sx
su_y_ksads__dud__reduce__dsr__stim__pres_sx
su_y_ksads__dud__reduce__unsucces__stim__pres_sx
su_y_ksads__dud__time__stim__pres_sx
su_y_ksads__dud__tol__stim__pres_sx
su_y_ksads__dud__withdr__stim__pres_sx
Excluded values:
555
Validation criterion: maximally 3 of 15 items missing
vars_su_y_ksads__dud__stim__pres__sx_mean compute_su_y_ksads__dud__stim__pres__sx_mean( data, name = "su_y_ksads__dud__stim__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )vars_su_y_ksads__dud__stim__pres__sx_mean compute_su_y_ksads__dud__stim__pres__sx_mean( data, name = "su_y_ksads__dud__stim__pres__sx_mean", max_na = 3, exclude = c("555"), combine = TRUE )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the summary score column. |
max_na |
numeric, positive whole number. Number of missing items
allowed. |
exclude |
character vector. Values to be excluded from the summary score calculation. |
combine |
logical. If |
vars_su_y_ksads__dud__stim__pres__sx_mean is a character vector
of all column names used to compute summary score of
su_y_ksads__dud__stim__pres__sx_mean
KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:
"888": item skipped by branching. When at least one input value is
observed, any 888 value is converted to "0" prior to averaging.
"555": module not administered. If any input variable is "555"
leave the score as NA.
NA: missing value. If at least one input value is observed,
any NA values are converted to "0" prior to averaging.
If all inputs are NA, the summary score remains NA.
tbl. see combine.
Computes the summary score su_y_mjexp__neg_prsum
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of negative
expectancies): Prorated sum [Validation: No more than 1
missing or declined]
Summarized variables:
su_y_mjexp__neg_001
su_y_mjexp__neg_002
su_y_mjexp__neg_003
Excluded values: none
Validation criterion: maximally 1 of 3 items missing
vars_su_y_mjexp__neg compute_su_y_mjexp__neg_prsum( data, name = "su_y_mjexp__neg_prsum", combine = TRUE, max_na = 1 )vars_su_y_mjexp__neg compute_su_y_mjexp__neg_prsum( data, name = "su_y_mjexp__neg_prsum", combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_mjexp__neg is a character vector of all column names
used to compute summary score of su_y_mjexp__neg_prsum and
su_y_mjexp__neg_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjexp__pos_prsum
Marijuana Expectancies (MEEQ-B) [Youth] (Strength of positive
expectancies): Prorated sum [Validation: No more than 1
missing or declined]
Summarized variables:
su_y_mjexp__pos_001
su_y_mjexp__pos_002
su_y_mjexp__pos_003
Excluded values: none
Validation criterion: maximally 1 of 3 items missing
vars_su_y_mjexp__pos compute_su_y_mjexp__pos_prsum( data, name = "su_y_mjexp__pos_prsum", combine = TRUE, max_na = 1 )vars_su_y_mjexp__pos compute_su_y_mjexp__pos_prsum( data, name = "su_y_mjexp__pos_prsum", combine = TRUE, max_na = 1 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_mjexp__pos is a character vector of all column names
used to compute summary score of su_y_mjexp__pos_prsum
and su_y_mjexp__pos_nm
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjprob_prsum
Marijuana Problem Index (MAPI) [Youth]: Prorated sum [Validation: No more
than 3 missing or declined]
Summarized variables:
su_y_mjprob_001
su_y_mjprob_002
su_y_mjprob_003
su_y_mjprob_004
su_y_mjprob_005
su_y_mjprob_006
su_y_mjprob_007
su_y_mjprob_008
su_y_mjprob_009
su_y_mjprob_010
su_y_mjprob_011
su_y_mjprob_012
su_y_mjprob_016
su_y_mjprob_017
su_y_mjprob_018
Excluded values: none
Validation criterion: maximally 3 items missing
vars_su_y_mjprob compute_su_y_mjprob_prsum( data, name = "su_y_mjprob_prsum", combine = TRUE, max_na = 3 )vars_su_y_mjprob compute_su_y_mjprob_prsum( data, name = "su_y_mjprob_prsum", combine = TRUE, max_na = 3 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_mjprob is a character vector of all column names
used to compute summary score of su_y_mjprob_prsum and
su_y_mjprob_nm.
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjsre_sum
Marijuana Subjective Response and Effects [Youth] (Total): Sum -
Positive score inverted [Validation: None missing or declined]
Summarized variables:
su_y_mjsre__pos_001
su_y_mjsre__pos_002
su_y_mjsre__pos_003
su_y_mjsre__neg_001
su_y_mjsre__neg_002
su_y_mjsre__neg_003
su_y_mjsre__neg_004
su_y_mjsre__neg_005
su_y_mjsre__neg_006
su_y_mjsre__neg_007
su_y_mjsre__neg_008
Excluded values: none
Validation criterion: maximally 0 of 11 items missing
vars_su_y_mjsre compute_su_y_mjsre_sum( data, name = "su_y_mjsre_sum", combine = TRUE, max_na = 0 )vars_su_y_mjsre compute_su_y_mjsre_sum( data, name = "su_y_mjsre_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_mjsre is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjsre__neg_sum
Marijuana Subjective Response and Effects [Youth] (Negative): Sum
[Validation: None missing or declined]
Summarized variables:
su_y_mjsre__neg_001
su_y_mjsre__neg_002
su_y_mjsre__neg_003
su_y_mjsre__neg_004
su_y_mjsre__neg_005
su_y_mjsre__neg_006
su_y_mjsre__neg_007
su_y_mjsre__neg_008
Excluded values: none
Validation criterion: maximally 0 of 8 items missing
vars_su_y_mjsre__neg compute_su_y_mjsre__neg_sum( data, name = "su_y_mjsre__neg_sum", combine = TRUE, max_na = 0 )vars_su_y_mjsre__neg compute_su_y_mjsre__neg_sum( data, name = "su_y_mjsre__neg_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_mjsre__neg is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre__neg (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_mjsre__pos_sum
Marijuana Subjective Response and Effects [Youth] (Positive): Sum
[Validation: None missing or declined]
Summarized variables:
su_y_mjsre__pos_001
su_y_mjsre__pos_002
su_y_mjsre__pos_003
Excluded values: none
Validation criterion: maximally 0 of 3 items missing
vars_su_y_mjsre__pos compute_su_y_mjsre__pos_sum( data, name = "su_y_mjsre__pos_sum", combine = TRUE, max_na = 0 )vars_su_y_mjsre__pos compute_su_y_mjsre__pos_sum( data, name = "su_y_mjsre__pos_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_mjsre__pos is a character vector of
all column names used to compute summary scores of
compute_su_y_mjsre__pos (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__chew_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first smokeless tobacco or chew use): Sum -
Negative score inverted [Validation: None missing or declined]
Summarized variables:
su_y_nicsre__chew__pos_001
su_y_nicsre__chew__neg_001
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
vars_su_y_nicsre__chew compute_su_y_nicsre__chew_sum( data, name = "su_y_nicsre__chew_sum", combine = TRUE, max_na = 0 )vars_su_y_nicsre__chew compute_su_y_nicsre__chew_sum( data, name = "su_y_nicsre__chew_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_nicsre__chew is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__chew (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__cig_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first cigarette use): Sum - Negative score
inverted [Validation: None missing or declined]
Summarized variables:
su_y_nicsre__cig__pos_001
su_y_nicsre__cig__neg_001
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
vars_su_y_nicsre__cig compute_su_y_nicsre__cig_sum( data, name = "su_y_nicsre__cig_sum", combine = TRUE, max_na = 0 )vars_su_y_nicsre__cig compute_su_y_nicsre__cig_sum( data, name = "su_y_nicsre__cig_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_nicsre__cig is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__cig (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicsre__vape_sum
Nicotine Subjective Response and Effects [Youth] (Intensity of
positive and negative effects of first vape use): Sum - Negative score
inverted [Validation: None missing or declined]
Summarized variables:
su_y_nicsre__vape__pos_001
su_y_nicsre__vape__pos_001__v01
su_y_nicsre__vape__neg_001
su_y_nicsre__vape__neg_001__v01
Excluded values: none
Validation criterion: maximally 0 of 2 items missing
vars_su_y_nicsre__vape compute_su_y_nicsre__vape_sum( data, name = "su_y_nicsre__vape_sum", combine = TRUE, max_na = 0 )vars_su_y_nicsre__vape compute_su_y_nicsre__vape_sum( data, name = "su_y_nicsre__vape_sum", combine = TRUE, max_na = 0 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character. Name of the new column to be created (Default: the name used in the ABCD data release). |
combine |
logical. If TRUE, the new column will be bound to the input data frame. If FALSE, the new column will be created as a new data frame. |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 0). |
vars_su_y_nicsre__vape is a character vector of
all column names used to compute summary scores of
compute_su_y_nicsre__vape (_sum, _nm).
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicvapeexp__neg_prsum
ENDS Expectancies [Youth] (Strength of negative expectancies):
Prorated sum [Validation: No more than 2 missing or declined]
Summarized variables:
su_y_nicvapeexp__neg_001
su_y_nicvapeexp__neg_002
su_y_nicvapeexp__neg_003
su_y_nicvapeexp__neg_004
Excluded values: none
Validation criterion: maximally 2 of 4 items missing
vars_su_y_nicvapeexp__neg compute_su_y_nicvapeexp__neg_prsum( data, name = "su_y_nicvapeexp__neg_prsum", combine = TRUE, max_na = 2 )vars_su_y_nicvapeexp__neg compute_su_y_nicvapeexp__neg_prsum( data, name = "su_y_nicvapeexp__neg_prsum", combine = TRUE, max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_nicvapeexp__neg is a character vector of all column names
used to compute summary score of su_y_nicvapeexp__neg_prsum and
su_y_nicvapeexp__neg_nm
tbl. The input data frame with the summary score appended as a new column.
Computes the summary score su_y_nicvapeexp__pos_prsum
ENDS Expectancies [Youth] (Strength of positive expectancies):
Prorated sum [Validation: No more than 2 missing or declined]
Summarized variables:
su_y_nicvapeexp__pos_001
su_y_nicvapeexp__pos_002
su_y_nicvapeexp__pos_003
su_y_nicvapeexp__pos_004
Excluded values: none
Validation criterion: maximally 2 of 4 items missing
vars_su_y_nicvapeexp__pos compute_su_y_nicvapeexp__pos_prsum( data, name = "su_y_nicvapeexp__pos_prsum", combine = TRUE, max_na = 2 )vars_su_y_nicvapeexp__pos compute_su_y_nicvapeexp__pos_prsum( data, name = "su_y_nicvapeexp__pos_prsum", combine = TRUE, max_na = 2 )
data |
tbl. Data frame containing the columns to be summarized. |
name |
character, Name of the new column to be created. Default is the name in description, but users can change it. |
combine |
logical, If |
max_na |
numeric, positive whole number. Number of missing items allowed (Default: 1). |
vars_su_y_nicvapeexp__pos is a character vector of all column names
used to compute summary score of su_y_nicvapeexp__pos_prsum and
su_y_nicvapeexp__pos_nm.
tbl. The input data frame with the summary score appended as a new column.