score_iip90: Score the Inventory for Interpersonal Problems - 90 items PD...

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

Score the Inventory for Interpersonal Problems – 90 items PD + circumplex version

Description

Score the Inventory for Interpersonal Problems – 90 items PD + circumplex version

Usage

score_iip90(
  df,
  item_prefix = "IIP_",
  max_impute = 0.2,
  drop_items = FALSE,
  drop_octants = FALSE,
  min_value = 0,
  max_value = 4,
  add_alphas = TRUE
)

Arguments

df	a data.frame containing the 90 IIP items to be scored
item_prefix	a character prefix of the items names in df to be scored. Default: "IIP"
max_impute	the proportion of missingness [0..1] or number [1..n] of missing values per subscale. Below this, the mean will be imputed for missing items.
drop_items	whether to remove the item-level data from the df. Default: FALSE
drop_octants	whether to remove the IIP octant scores. Default: FALSE
min_value	the lowest value for the items anchors, used to check response validity. Default: 0
max_value	the highest value for the items anchors, used to check response validity. Default: 4
add_alphas	whether to compute coefficient alpha for subscales and return a column attribute. Default: TRUE

Details

Adds twenty columns, eight for octant scales, six for pd scales, and six for circumplex scales, to df containing the octant, pd, and additional scales, respectively.

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

Note: the code assumes that pasting together the item_prefix and the numbers 1:90 will yield the 90 items from the test.

Author(s)

Michael Hallquist

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