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:	0.2.0
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, ggplot2 (≥ 3.4.0), forcats
Suggests:	ggrepel, patchwork, eRm, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-03-28
DOI:	10.32614/CRAN.package.easyRaschBayes
Author:	Magnus Johansson [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, https://pgmj.github.io/easyRaschBayes/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	easyRaschBayes results

Documentation:

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

Downloads:

Package source:	easyRaschBayes_0.2.0.tar.gz
Windows binaries:	r-devel: easyRaschBayes_0.2.0.zip, r-release: easyRaschBayes_0.2.0.zip, r-oldrel: easyRaschBayes_0.2.0.zip
macOS binaries:	r-release (arm64): easyRaschBayes_0.2.0.tgz, r-oldrel (arm64): easyRaschBayes_0.1.0.tgz, r-release (x86_64): easyRaschBayes_0.2.0.tgz, r-oldrel (x86_64): easyRaschBayes_0.2.0.tgz
Old sources:	easyRaschBayes archive

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