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MultiLCIRT (version 2.11)

Multidimensional Latent Class Item Response Theory Models

Description

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).

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Version

Install

install.packages('MultiLCIRT')

Monthly Downloads

650

Version

2.11

License

GPL (>= 2)

Maintainer

Francesco Bartolucci

Last Published

June 6th, 2017

Functions in MultiLCIRT (2.11)

MultiLCIRT-package

Multidimensional Latent Class (LC) Item Response Theory (IRT) Models
aggr_data

Aggregate data
est_multi_glob

Fit marginal regression models for categorical responses
est_multi_poly

Estimate multidimensional LC IRT model for dichotomous and polytomous responses
class_item

Hierarchical classification of test items
compare_models

Compare different models fitted by est_multi_poly
inv_glob

Invert marginal logits
lk_obs_score

Compute observed log-likelihood and score
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
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
naep

NAEP dataset
print.class_item

Print the output of class_item object
test_dim

Likelihood ratio testing between nested multidimensional LC IRT models
summary.class_item

Print the output of class_item object
summary.est_multi_poly

Print the output of test_dim 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
summary.est_multi_poly_clust

Print the output of est_multi_poly_clust object
summary.test_dim

Print the output of test_dim object
matr_glob

Matrices to compute generalized logits
lk_obs_score_clust

Compute observed log-likelihood and score