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 LICENSE NeedsCompilation: yes Language: en-US Materials: README CRAN checks: IRTM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=IRTM to link to this page.
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