permutation_sctest: A score-based DIF test using the permutation approach.
In ddebeer/Rsctest: Resampling Score-Based Test for DIF-Detection

Description Usage Arguments Value See Also

View source: R/permutation_sctest.R

permutation_sctest computes score test to detect DIF in multiple item/parameters with respect to multiple person covariates (DIF_covariate). To obtain the p-values a resampling approach is applied. That is, person orders are randomly permuted to sample from the test statistic distribution under the null hypothesis. The functionality is limited to the 1-, 2-, and 3-parameter logistic models. Only DIF with respect to the a and b parameters are tested for, respectively the item discriminations and the item difficulties.

permutation_sctest(
  resp,
  theta = NULL,
  a = rep(1, length(b)),
  b,
  c = rep(0, length(b)),
  DIF_covariate = NULL,
  parameters = c("per_item", "ab", "a", "b"),
  item_selection = NULL,
  nSamples = 1000,
  theta_method = c("wle", "mle", "eap", "map"),
  slope_intercept = FALSE,
  statistic = "auto",
  meanCenter = TRUE,
  decorrelate = FALSE,
  impact_groups = rep(1, dim(resp)[1])
)

`resp`	A matrix (or data frame) containing the responses, with the items in the columns.
`theta`	A vector with the true/estimated ability parameters or NULL (the default) which leads to the ability parameters being estimated.
`a`	A vector of item slopes/item discriminations.
`b`	A vector of item locations/item difficulties.
`c`	A vector of pseudo guessing parameters.
`DIF_covariate`	A list with the person covariate(s) to test for as element(s).
`parameters`	A charachter string, either "per_item", "ab", "a", or "b", to specify which parameters should be tested for.
`item_selection`	A character vector with the colum names or an integer vector with the colum numbers in the `resp`, specifying the items for which the test should be computed. When set to NULL (i.t., the default), all the items are tested.
`nSamples`	An integer value with the number of permutations to be sampled.
`theta_method`	A charachter string, either "wle", "mle", "eap", of "map" that specifies the estimator for the ability estimation. Only relevant when `theta == NULL`.
`slope_intercept`	A logical value indicating whether the slope-intercept formulation of the 2-/3-PL model should be used.
`statistic`	A charachter string, either "auto", "DM", "CvM", "maxLM", "LMuo", "WDMo", or "maxLMo", specifying the test statistic to be used.
`meanCenter`	A logical value: should the score contributions be mean centered per parameter?
`decorrelate`	A logical value: should the score contributions be decorrelated?
`impact_groups`	A vector indicating impact-group membership for each person.

a list with four elements:

statistics: A matrix containing all the test statistics.
p: A matrix containing the obtained p-values.
nSamples: The number of samples taken.
DIF_covariate: A list containing all the covariate(s) used to order the score contirbutions, as well as the used test statistics.