score_paibor: Score PAI-BOR subscales for affective instability, indentity...

In PennStateDEPENdLab/dependlab: Useful functions for the UNC Chapel Hill DEPENd Lab (Director: Michael Hallquist)

Score PAI-BOR subscales for affective instability, indentity problems, negative relationships, and self-harm

Description

This function scores the PAI-BOR subscales for all subject IDs in the tracker tab of the master spreadsheet.

Usage

score_paibor(
  df,
  item_prefix = "PAIBOR_",
  max_impute = 0.2,
  min_value = 0,
  max_value = 3
)

Arguments

df	dataframe containing the PAI-BOR items to be scored
item_prefix	a character prefix of the items names in df to be scored. Default: "PAIBOR_"
max_impute	the proportion of missingness [0..1) or number [1..n] of missing values per scale. Below this threshold, the person subscale mean will be imputed for missing items.
min_value	the minimum value for the item anchors, used in reverse scoring. Default: 0
max_value	the highest value for the item anchors, used in reverse scoring. Default: 3

Value

A data frame with the PAI-BOR subscales scores and total PAI-BOR score

Author(s)

Nidhi Desai

PennStateDEPENdLab/dependlab documentation built on April 10, 2024, 5:15 p.m.