IRTM: Theory-Driven Item Response Theory (IRT) Models (original) (raw)
IRT-M is a semi-supervised approach based on Bayesian Item Response Theory that produces theoretically identified underlying dimensions from input data and a constraints matrix. The methodology is fully described in 'Morucci et al. (2024), "Measurement That Matches Theory: Theory-Driven Identification in Item Response Theory Models"'. Details are available at <https://www.cambridge.org/core/journals/american-political-science-review/article/measurement-that-matches-theory-theorydriven-identification-in-item-response-theory-models/395DA1DFE3DCD7B866DC053D7554A30B>.
| Version: | 0.0.1.1 |
|---|---|
| Depends: | truncnorm, tmvtnorm, utils, RcppProgress, RcppDist, ggplot2, R (≥ 3.5.0) |
| Imports: | coda, Rcpp, RcppArmadillo, ggridges, rlang, dplyr, reshape2 |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist, RcppProgress |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), RColorBrewer, fastDummies, ggrepel, tidyverse, spelling |
| Published: | 2025-04-19 |
| DOI: | 10.32614/CRAN.package.IRTM |
| Author: | Marco Morucci [aut], Margaret Foster  [cre], David Siegel [aut] |
| Maintainer: | Margaret Foster <m.jenkins.foster at gmail.com> |
| License: | MIT + file |
| NeedsCompilation: | yes |
| Language: | en-US |
| Materials: | README |
| CRAN checks: | IRTM results |
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