score_panas: Score the Positive and Negative Affect Schedule (PANAS) scale

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

Score the Positive and Negative Affect Schedule (PANAS) scale

Description

Score the Positive and Negative Affect Schedule (PANAS) scale

Usage

score_panas(
  df,
  item_prefix = "PANAS_",
  max_impute = 0.2,
  drop_items = FALSE,
  min_value = 1,
  max_value = 5,
  bad_items = NULL,
  add_alphas = TRUE
)

Arguments

df	a data.frame containing the 20 PANAS items to be scored
item_prefix	a character prefix of the items names in df to be scored. Default: "PANAS"
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: 5
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 two columns, PANAS_positive and PANAS_negative, to df containing the positive and negative affect scales, respectively.

Note: the default PANAS scoring uses the sum of the items for the scales.

Note: the code assumes that pasting together the item_prefix and the numbers 1:20 will yield the 20 items from the test.

Author(s)

Michael Hallquist, Zach Vig

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