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Compute "Prodromal Psychosis Scale [Youth] (number of "Yes" responses): Count "

Source: R/scores_mh.R
compute_mh_y_pps_count.Rd

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

Usage

vars_mh_y_pps_count

compute_mh_y_pps_count(
  data,
  name = "mh_y_pps_count",
  max_na = 4,
  combine = TRUE
)

Format

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

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.

max_na

integer, Maximum number of missing values allowed in the summary score.

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.

Value

tbl. The input data frame with the summary score appended as a new column.

Details

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%).

Examples

if (FALSE) { # \dontrun{
compute_mh_y_pps_count(data) |>
  select(
    any_of(c("mh_y_pps_count", vars_mh_y_pps_count))
  )
} # }