Package: hIRT 0.4.0
hIRT: Hierarchical Item Response Theory Models
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.
Authors:
hIRT_0.4.0.tar.gz
hIRT_0.4.0.zip(r-4.5)hIRT_0.4.0.zip(r-4.4)
hIRT_0.4.0.tgz(r-4.4-any)
hIRT_0.4.0.tar.gz(r-4.5-noble)hIRT_0.4.0.tar.gz(r-4.4-noble)
hIRT_0.4.0.tgz(r-4.4-emscripten)
hIRT.pdf |hIRT.html✨
hIRT/json (API)
NEWS
# Install 'hIRT' in R: |
install.packages('hIRT', repos = c('https://xiangzhou09.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/xiangzhou09/hirt/issues
- nes_econ2008 - Public Attitudes on Economic Issues in ANES 2008
Last updated 3 years agofrom:b33d90f132. Checks:OK: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win | OK | Nov 08 2024 |
R-4.5-linux | OK | Nov 08 2024 |
R-4.4-win | OK | Nov 08 2024 |
R-4.4-mac | OK | Nov 08 2024 |
Exports:coef_itemcoef_meancoef_varhgrmhgrm2hgrmDIFhltmhltm2latent_scores
Dependencies:admiscbackportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecpp11crayondata.tabledigestevaluateexpmfansifarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelobstrltmmagrittrMASSMatrixMatrixModelsmemoisemgcvmimemsmmultcompmunsellmvtnormnlmennetpillarpkgconfigpolsplinepolycorprettyunitspryrquantregR6rappdirsRColorBrewerRcpprlangrmarkdownrmsrpartrstudioapisandwichsassscalesSparseMstringistringrsurvivalTH.datatibbletinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo