Package: easyRaschBayes
Title: Bayesian Rasch Analysis Using 'brms'
Version: 0.2.0.1
Authors@R: c(
    person("Magnus", "Johansson",
           role = c("aut", "cre"),
           email = "pgmj@pm.me",
           comment = c(ORCID = "0000-0003-1669-592X")),
    person("Giacomo", "Bignardi",
           role = "ctb",
           comment = "RMU reliability code"))
Description: 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>.
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
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
URL: https://github.com/pgmj/easyRaschBayes,
        https://pgmj.github.io/easyRaschBayes/
BugReports: https://github.com/pgmj/easyRaschBayes/issues
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-04-23 06:45:31 UTC; magnus.johansson.3
Author: Magnus Johansson [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-1669-592X>),
  Giacomo Bignardi [ctb] (RMU reliability code)
Maintainer: Magnus Johansson <pgmj@pm.me>
Repository: CRAN
Date/Publication: 2026-04-23 07:10:02 UTC
Built: R 4.6.0; ; 2026-04-26 17:49:07 UTC; unix
