Multidimensional Latent Class Item Response Theory Models
Aggregate data
Hierarchical classification of test items
Compare different models fitted by est_multi_poly
Fit marginal regression models for categorical responses
Estimate multidimensional LC IRT model for dichotomous and polytomous ...
Estimate multidimensional and multilevel LC IRT model for dichotomous ...
Invert marginal logits
Compute observed log-likelihood and score
Compute observed log-likelihood and score
Matrices to compute generalized logits
Multidimensional Latent Class (LC) Item Response Theory (IRT) Models
Print the output of class_item object
Print the output of est_multi_poly object
Print the output of est_multi_poly_clust object
Print the output of test_dim object
Global probabilities
Search for the global maximum of the log-likelihood
Standardization of a matrix of support points on the basis of a vector...
Print the output of class_item object
Print the output of test_dim object
Print the output of est_multi_poly_clust object
Print the output of test_dim object
Likelihood ratio testing between nested multidimensional LC IRT models
Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parameterizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version (since 2.1).