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) . 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.


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install.packages("GPCMlasso")

0.1-4 by Gunther Schauberger, 8 months ago


Browse source code at https://github.com/cran/GPCMlasso


Authors: Gunther Schauberger


Documentation:   PDF Manual  


Task views: Psychometric Models and Methods


GPL (>= 2) license


Imports Rcpp, TeachingDemos, cubature, caret, statmod, mvtnorm, mirt, methods

Depends on ltm

Linking to Rcpp, RcppArmadillo

System requirements: C++11


Enhanced by mnlfa.


See at CRAN