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)