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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>.
Getting started
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Package details |
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| Author | Kosuke Imai <imai@harvard.edu>, James Lo <jameslo989@gmail.com>, Jonathan Olmsted <jpolmsted@gmail.com> |
| Maintainer | Kosuke Imai <imai@harvard.edu> |
| License | GPL (>= 3) |
| Version | 0.0.14 |
| Package repository | View on CRAN |
| Installation |
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