Compute "Prodromal Psychosis Scale [Youth] (Severity Score): Number missing"

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

Usage

vars_mh_y_pps__severity

compute_mh_y_pps__severity_nm(
  data,
  name = "mh_y_pps__severity_nm",
  combine = TRUE
)

Format

vars_mh_y_pps__severity is a character vector of all column names used to compute summary of mh_y_pps__severity 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__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.

See also

compute_mh_y_pps__bother__yes_count()

Examples

if (FALSE) { # \dontrun{
compute_mh_y_pps__severity_nm(data) |>
  select(
    any_of(c("mh_y_pps__severity_nm", vars_mh_y_pps__severity))
  )
} # }