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 |