easyRaschBayes: Bayesian Rasch Analysis Using 'brms'

Reproduces classic Rasch psychometric analysis features using Bayesian item response theory models fitted with 'brms' following Bürkner (2021) <doi:10.18637/jss.v100.i05> and Bürkner (2020) <doi:10.3390/jintelligence8010005>. Supports both dichotomous and polytomous Rasch models. Features include posterior predictive item fit, conditional infit, item-restscore associations, person fit, differential item functioning, local dependence assessment via Q3 residual correlations, dimensionality assessment with residual principal components analysis, person-item targeting plots, item category probability curves, and reliability using relative measurement uncertainty following Bignardi et al. (2025) <doi:10.31234/osf.io/h54k8_v1>.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: brms (≥ 2.20.0), rlang (≥ 1.0.0), dplyr (≥ 1.1.0), tidyr (≥ 1.3.0), tibble (≥ 3.0.0), ggdist, stats, grDevices
Suggests: ggplot2 (≥ 3.4.0), ggrepel, patchwork, eRm, testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-03-11
DOI: 10.32614/CRAN.package.easyRaschBayes (may not be active yet)
Author: Magnus Johansson ORCID iD [aut, cre], Giacomo Bignardi [ctb] (RMU reliability code)
Maintainer: Magnus Johansson <pgmj at pm.me>
BugReports: https://github.com/pgmj/easyRaschBayes/issues
License: GPL (≥ 3)
URL: https://github.com/pgmj/easyRaschBayes
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: easyRaschBayes results

Documentation:

Reference manual: easyRaschBayes.html , easyRaschBayes.pdf
Vignettes: Partial Credit Model Analysis with easyRaschBayes (source)

Downloads:

Package source: easyRaschBayes_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): easyRaschBayes_0.1.0.tgz, r-oldrel (arm64): easyRaschBayes_0.1.0.tgz, r-release (x86_64): easyRaschBayes_0.1.0.tgz, r-oldrel (x86_64): easyRaschBayes_0.1.0.tgz

Linking:

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