Regularized Explanatory Generalized Partial Credit Models R package GPCMlasso version 0.2-0 CRAN Task View: Psychometrics (https://CRAN.R-project.org/view=Psychometrics) Fits explanatory generalized partial credit models and related ordinal item response models with global and item-specific covariate effects. Penalized marginal maximum likelihood estimation is used for variable selection, detection of differential item functioning, and clustering of item-specific covariate effects by fusion penalties. The package extends the regularization approach for differential item functioning in generalized partial credit models proposed by Schauberger and Mair (2020) <doi:10.3758/s13428-019-01224-2>. Software Depends: ltm Imports: Rcpp (>= 0.12.4), TeachingDemos, cubature, caret, statmod, mvtnorm, mirt, methods LinkingTo: Rcpp, RcppArmadillo Gunther Schauberger <gunther.schauberger@tum.de> Comprehensive R Archive Network (CRAN) Gunther Schauberger [aut, cre] GPL (>= 2) 2026-09-08 application/tgz https://CRAN.R-project.org/package=GPCMlasso doi:10.32614/CRAN.package.GPCMlasso