| MultiLCIRT-package | Multidimensional Latent Class (LC) Item Response Theory (IRT) Models |
| aggr_data | Aggregate data |
| class_item | Hierarchical classification of test items |
| compare_models | Compare different models fitted by est_multi_poly |
| est_multi_glob | Fit marginal regression models for categorical responses |
| est_multi_poly | Estimate multidimensional LC IRT model for dichotomous and polytomous responses |
| est_multi_poly_clust | Estimate multidimensional and multilevel LC IRT model for dichotomous and polytomous responses |
| hads | Dataset about measurement of anxiety and depression in oncological patients |
| inv_glob | Invert marginal logits |
| lk_obs_score | Compute observed log-likelihood and score |
| lk_obs_score_clust | Compute observed log-likelihood and score |
| matr_glob | Matrices to compute generalized logits |
| MultiLCIRT | Multidimensional Latent Class (LC) Item Response Theory (IRT) Models |
| naep | NAEP dataset |
| print.class_item | Print the output of class_item object |
| print.est_multi_poly | Print the output of est_multi_poly object |
| print.est_multi_poly_clust | Print the output of est_multi_poly_clust object |
| print.test_dim | Print the output of test_dim object |
| prob_multi_glob | Global probabilities |
| search.model | Search for the global maximum of the log-likelihood |
| standard.matrix | Standardization of a matrix of support points on the basis of a vector of probabilities |
| summary.class_item | Print the output of class_item object |
| summary.est_multi_poly | Print the output of test_dim object |
| summary.est_multi_poly_clust | Print the output of est_multi_poly_clust object |
| summary.test_dim | Print the output of test_dim object |
| test_dim | Likelihood ratio testing between nested multidimensional LC IRT models |