score_ders: Score the Difficulties in Emotion Regulation Scale (DERS)...

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

Score the Difficulties in Emotion Regulation Scale (DERS) (Gratz & Roemer, 2004)

Description

Score the Difficulties in Emotion Regulation Scale (DERS) (Gratz & Roemer, 2004)

Usage

score_ders(
  df,
  item_prefix = "DERS",
  max_impute = 0.2,
  drop_items = FALSE,
  keep_reverse_codes = FALSE,
  min_value = 1,
  max_value = 5
)

Arguments

df	a data.frame containing the 36 DERS items to be scored
item_prefix	a character prefix of the items names in df to be scored. Default: "DERS"
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
keep_reverse_codes	whether to retain the reverse coded items (suffix "r")
min_value	the minimum value for the item anchors, used in reverse scoring. Default: 1
max_value	the highest value for the item anchors, used in reverse scoring. Default: 5

Details

Adds seven columns, DERS_nonaccept, DERS_goals, DERS_impulse, DERS_aware, DERS_strategies, DERS_clarity, and DERS_total, to df containing the different subscales, respectively.

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

Note: the code assumes that pasting together the item_prefix and the numbers 1:36 will yield the 36 items from the test.

Author(s)

Michael Hallquist

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