ABCDscores (version 6.1.0)

vars_mh_y_pps__bother: Compute "Prodromal Psychosis Scale [Youth] (Bother responses): Number missing"

Description

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

Usage

vars_mh_y_pps__bother
compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)

Format

vars_mh_y_pps__bother is a character vector of all column names used to compute summary of mh_y_pps__bother scores.

Arguments

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 TRUE, the summary score will be appended to the input data frame. If FALSE, the summary score will be returned as a separate data frame.

Details

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.

See Also

compute_mh_y_pps_count()

Examples

if (FALSE) {
compute_mh_y_pps__bother_nm(data) |>
  select(
    any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother))
  )
}