MultiLCIRT: Multidimensional Latent Class Item Response Theory Models

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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).

Author
Francesco Bartolucci, Silvia Bacci, Michela Gnaldi - University of Perugia (IT)
Date of publication
2016-04-13 09:27:59
Maintainer
Francesco Bartolucci <bart@stat.unipg.it>
License
GPL (>= 2)
Version
2.10

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Man pages

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...
est_multi_poly_clust
Estimate multidimensional and multilevel LC IRT model for...
hads
Dataset about measurement of anxiety and depression in...
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-package
Multidimensional Latent Class (LC) Item Response Theory (IRT)...
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...
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...

Files in this package

MultiLCIRT
MultiLCIRT/src
MultiLCIRT/src/aggrdata.f
MultiLCIRT/src/lk_obs.f
MultiLCIRT/NAMESPACE
MultiLCIRT/data
MultiLCIRT/data/hads.RData
MultiLCIRT/data/naep.RData
MultiLCIRT/R
MultiLCIRT/R/prob_multi_glob.R
MultiLCIRT/R/lk_obs_score.R
MultiLCIRT/R/est_multi_poly_clust.R
MultiLCIRT/R/search.model.R
MultiLCIRT/R/summary.test_dim.R
MultiLCIRT/R/test_dim.R
MultiLCIRT/R/print.test_dim.R
MultiLCIRT/R/summary.est_multi_poly.R
MultiLCIRT/R/print.est_multi_poly.R
MultiLCIRT/R/lk_obs_score_clust.R
MultiLCIRT/R/summary.est_multi_poly_clust.R
MultiLCIRT/R/compare_models.R
MultiLCIRT/R/class_item.R
MultiLCIRT/R/inv_glob.R
MultiLCIRT/R/est_multi_poly.R
MultiLCIRT/R/aggr_data.R
MultiLCIRT/R/print.class_item.R
MultiLCIRT/R/summary.class_item.R
MultiLCIRT/R/est_multi_glob.R
MultiLCIRT/R/print.est_multi_poly_clust.R
MultiLCIRT/R/matr_glob.R
MultiLCIRT/R/standard.matrix.R
MultiLCIRT/MD5
MultiLCIRT/DESCRIPTION
MultiLCIRT/man
MultiLCIRT/man/print.est_multi_poly_clust.Rd
MultiLCIRT/man/search.model.Rd
MultiLCIRT/man/MultiLCIRT-package.Rd
MultiLCIRT/man/matr_glob.Rd
MultiLCIRT/man/compare_models.Rd
MultiLCIRT/man/standard.matrix.Rd
MultiLCIRT/man/print.class_item.Rd
MultiLCIRT/man/print.test_dim.Rd
MultiLCIRT/man/summary.class_item.Rd
MultiLCIRT/man/est_multi_poly_clust.Rd
MultiLCIRT/man/est_multi_poly.Rd
MultiLCIRT/man/lk_obs_score_clust.Rd
MultiLCIRT/man/test_dim.Rd
MultiLCIRT/man/lk_obs_score.Rd
MultiLCIRT/man/est_multi_glob.Rd
MultiLCIRT/man/naep.Rd
MultiLCIRT/man/summary.test_dim.Rd
MultiLCIRT/man/summary.est_multi_poly_clust.Rd
MultiLCIRT/man/print.est_multi_poly.Rd
MultiLCIRT/man/inv_glob.Rd
MultiLCIRT/man/hads.Rd
MultiLCIRT/man/prob_multi_glob.Rd
MultiLCIRT/man/summary.est_multi_poly.Rd
MultiLCIRT/man/aggr_data.Rd
MultiLCIRT/man/class_item.Rd