score_isc: Score the Interpersonal Stressors Circumplex (ISC)

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

Score the Interpersonal Stressors Circumplex (ISC)

Description

Score the Interpersonal Stressors Circumplex (ISC)

Usage

score_isc(
  df,
  item_prefix = "ISC_",
  max_impute = 0.2,
  drop_items = FALSE,
  min_value = 1,
  max_value = 8,
  bad_items = NULL,
  add_alphas = TRUE
)

Arguments

df	a data.frame containing the 64 ISC items to be scored
item_prefix	a character prefix of the items names in df to be scored. Default: "ISC"
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.
drop_items	whether to remove the item-level data from the df. Default: FALSE
min_value	the minimum value for the item anchors. Default: 1
max_value	the highest value for the item anchors. Default: 8
bad_items	numeric value or vector of the items that need to be dropped before imputation or calculation of subscales
add_alphas	whether to compute coefficient alpha for the total scale and return a column attribute. Default: TRUE

Details

Adds eight columns, ISC_c1, ISC_c2, ISC_c3, ISC_c4, ISC_c5, ISC_c6, ISC_c7, and ISC_c8, to df containing the different subscales, respectively.

Note: the default ISC scoring uses the mean of the items for the scales.

Note: the code assumes that pasting together the item_prefix and the numbers 1:64 will yield the 64 items from the test.

Author(s)

Michael Hallquist, Zach Vig

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