test_respca: runs a principal component analysis (PCA) on the residuals of...

In exhaustiveRasch: Item Selection and Exhaustive Search for Rasch Models

runs a principal component analysis (PCA) on the residuals of the rasch model.

Description

runs a principal component analysis (PCA) on the residuals of the rasch model.

Usage

test_respca(
  items = NULL,
  dset = NULL,
  na.rm = TRUE,
  model = NULL,
  p.par = NULL,
  modelType = NULL,
  max_contrast = 1.5,
  estimation_param = NULL
)

Arguments

items	a numeric vector containing the index numbers of the items in dset that are used to fit the model
dset	a data.frame containing the data
na.rm	a boolean value. If TRUE, all cases with any NA are removed (na.omit). If FALSE, only cases with full NA responses are removed
model	on object of a fit Rasch model, estimated with the packages 'eRm' (classes 'RM', 'PCM' or 'RSM'), 'psychotools' (classes raschmodel, 'pcmodel' or 'rsmodel') or 'pairwise' (class 'pers'), matching the value of modelType. If 'model' is provided, this model is used. If NULL, a model is fit using 'dset' and 'items'.
p.par	a person parameter object matching the class of 'model'. If NULL, the person parameters will be estimated.
modelType	a character value defining the rasch model to fit. Possible values: "RM", "PCM", "RSM".
max_contrast	a numeric value defining the maximum loading of a factor in the principal components analysis of the standardised residuals.
estimation_param	options for parameter estimation using estimation_control

Value

if the maximum eigenvalue of the contrasts of the pca is < max_contrast, a list containing 3 elements is returned: the item combination that was tested, a list of the class the model was estimated with (depending on modelType and estimation_param$est) with the fit model and a list with a person parameter object (depending on estimation_param$est). Else, NULL is returned.

exhaustiveRasch documentation built on April 3, 2025, 6:18 p.m.