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: |
0.0.15 |
Depends: |
R (≥ 2.10), pscl (≥ 1.0.0), Rcpp (≥ 0.10.6) |
LinkingTo: |
Rcpp, RcppArmadillo |
Suggests: |
MCMCpack |
Published: |
2025-09-23 |
Author: |
Kosuke Imai [aut, cre],
James Lo [aut],
Jonathan Olmsted [aut] |
Maintainer: |
Kosuke Imai <imai at harvard.edu> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
yes |
Materials: |
ChangeLog |
CRAN checks: |
emIRT results [issues need fixing before 2025-10-23] |
Documentation:
Downloads:
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