emIRT: EM Algorithms for Estimating Item Response Theory Models

Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The package includes IRT models for binary and ordinal responses, along with dynamic and hierarchical IRT models with binary responses. The latter two models are fitted using variational EM. The package also includes variational network and text scaling models. The algorithms are described in Imai, Lo, and Olmsted (2016) <doi:10.1017/S000305541600037X>.

Version: 0.0.13
Depends: R (≥ 2.10), pscl (≥ 1.0.0), Rcpp (≥ 0.10.6)
LinkingTo: Rcpp, RcppArmadillo
Suggests: MCMCpack
Published: 2022-03-04
Author: Kosuke Imai, James Lo, Jonathan Olmsted
Maintainer: James Lo <lojames at usc.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: emIRT results


Reference manual: emIRT.pdf


Package source: emIRT_0.0.13.tar.gz
Windows binaries: r-devel: emIRT_0.0.13.zip, r-release: emIRT_0.0.13.zip, r-oldrel: emIRT_0.0.13.zip
macOS binaries: r-release (arm64): emIRT_0.0.13.tgz, r-oldrel (arm64): emIRT_0.0.13.tgz, r-release (x86_64): emIRT_0.0.13.tgz, r-oldrel (x86_64): emIRT_0.0.13.tgz
Old sources: emIRT archive


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