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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>.
| Version: | 0.2-0 |
| Depends: | ltm |
| Imports: | Rcpp (≥ 0.12.4), TeachingDemos, cubature, caret, statmod, mvtnorm, mirt, methods |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2026-09-08 |
| DOI: | 10.32614/CRAN.package.GPCMlasso |
| Author: | Gunther Schauberger [aut, cre] |
| Maintainer: | Gunther Schauberger <gunther.schauberger at tum.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| In views: | Psychometrics |
| CRAN checks: | GPCMlasso results |
| Reference manual: | GPCMlasso.html , GPCMlasso.pdf |
| Package source: | GPCMlasso_0.2-0.tar.gz |
| Windows binaries: | r-devel: GPCMlasso_0.2-0.zip, r-release: GPCMlasso_0.2-0.zip, r-oldrel: GPCMlasso_0.2-0.zip |
| macOS binaries: | r-release (arm64): GPCMlasso_0.1-9.tgz, r-oldrel (arm64): GPCMlasso_0.2-0.tgz, r-release (x86_64): GPCMlasso_0.2-0.tgz, r-oldrel (x86_64): GPCMlasso_0.2-0.tgz |
| Old sources: | GPCMlasso archive |
| Reverse enhances: | mnlfa |
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