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Implementation of a class of hierarchical item response theory (IRT) models where both the mean and the variance of latent preferences (ability parameters) may depend on observed covariates. The current implementation includes both the two-parameter latent trait model for binary data and the graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) algorithm. Asymptotic standard errors are derived from the observed information matrix.
Version: | 0.3.0 |
Depends: | R (≥ 3.4.0), stats |
Imports: | pryr (≥ 0.1.2), rms (≥ 5.1-1), ltm (≥ 1.1-1), Matrix (≥ 1.2-10) |
Suggests: | ggplot2 (≥ 2.2.1), knitr, rmarkdown |
Published: | 2020-03-26 |
DOI: | 10.32614/CRAN.package.hIRT |
Author: | Xiang Zhou [aut, cre] |
Maintainer: | Xiang Zhou <xiang_zhou at fas.harvard.edu> |
BugReports: | http://github.com/xiangzhou09/hIRT |
License: | GPL (≥ 3) |
URL: | http://github.com/xiangzhou09/hIRT |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | hIRT results |
Reference manual: | hIRT.pdf |
Package source: | hIRT_0.3.0.tar.gz |
Windows binaries: | r-devel: hIRT_0.3.0.zip, r-release: hIRT_0.3.0.zip, r-oldrel: hIRT_0.3.0.zip |
macOS binaries: | r-release (arm64): hIRT_0.3.0.tgz, r-oldrel (arm64): hIRT_0.3.0.tgz, r-release (x86_64): hIRT_0.3.0.tgz, r-oldrel (x86_64): hIRT_0.3.0.tgz |
Old sources: | hIRT archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.