GPCMlasso: Differential Item Functioning in Generalized Partial Credit Models

Provides a framework to detect Differential Item Functioning (DIF) in Generalized Partial Credit Models (GPCM) and special cases of the GPCM as proposed by Schauberger and Mair (2019) <doi:10.3758/s13428-019-01224-2>. A joint model is set up where DIF is explicitly parametrized and penalized likelihood estimation is used for parameter selection. The big advantage of the method called GPCMlasso is that several variables can be treated simultaneously and that both continuous and categorical variables can be used to detect DIF.

Version:	0.1-6
Depends:	ltm
Imports:	Rcpp (≥ 0.12.4), TeachingDemos, cubature, caret, statmod, mvtnorm, mirt, methods
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	gvcm.cat
Published:	2022-05-03
Author:	Gunther Schauberger
Maintainer:	Gunther Schauberger <gunther.schauberger at tum.de>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
SystemRequirements:	C++11
In views:	Psychometrics
CRAN checks:	GPCMlasso results

Documentation:

Reference manual:

GPCMlasso.pdf

Downloads:

Package source:	GPCMlasso_0.1-6.tar.gz
Windows binaries:	r-devel: GPCMlasso_0.1-6.zip, r-release: GPCMlasso_0.1-6.zip, r-oldrel: GPCMlasso_0.1-6.zip
macOS binaries:	r-release (arm64): GPCMlasso_0.1-6.tgz, r-oldrel (arm64): GPCMlasso_0.1-6.tgz, r-release (x86_64): GPCMlasso_0.1-6.tgz, r-oldrel (x86_64): GPCMlasso_0.1-6.tgz
Old sources:	GPCMlasso archive

Reverse dependencies:

Reverse enhances:

mnlfa

Linking:

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