Package: easyRasch2
Title: Psychometric Analysis with Rasch Measurement Theory
Version: 1.4.0
Authors@R: c(
    person("Magnus", "Johansson",
           role = c("aut", "cre"),
           email = "pgmj@pm.me",
           comment = c(ORCID = "0000-0003-1669-592X")),
    person("Nicklas", "Korsell",
           role = "ctb",
           comment = "PCM simulation code"),
    person("Mirka", "Henninger",
           role = "ctb",
           comment = c(ORCID = "0000-0003-4676-2361",
           "MH / partial-gamma effect-size and ETS-classification algorithms in dif_tree.R, adapted under MIT licence from the raschtreeMH and effecttree packages")),
    person("Jan", "Radek",
           role = "ctb",
           comment = c(ORCID = "0009-0003-8842-9206",
           "partial-gamma effect-size and ETS-classification algorithms in dif_tree.R, adapted under MIT licence from the effecttree package")))
Description: Streamlines reproducible Rasch measurement theory analyses
        for ordinal item-response data, combining estimation routines
        from 'eRm', 'psychotools', 'mirt', 'iarm', and 'lavaan' with
        consistent diagnostic, plotting, and reporting layers. Covers
        the four basic psychometric criteria summarised by Christensen
        et al. (2021) <doi:10.1111/sms.13908> -- unidimensionality,
        local independence, ordered response category thresholds, and
        invariance across subgroups -- together with item fit,
        targeting, reliability, category functioning, and descriptive
        item-response plots. A distinguishing feature is the use of
        simulation-based critical values to replace rule-of-thumb
        cutoffs for conditional infit mean-square, item-rest-score
        gamma, Yen's Q3 local-dependence statistic, the largest
        residual-PCA eigenvalue, ordinal CFA fit indices, and
        partial-gamma DIF and local-dependence coefficients, optionally
        augmented with multiplicity-corrected bootstrap p-values.
        Outputs are knitr::kable() tables and 'ggplot2' figures
        suitable for direct inclusion in 'Quarto' and 'R Markdown'
        reports.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
URL: https://github.com/pgmj/easyRasch2,
        https://pgmj.github.io/easyRasch2/
BugReports: https://github.com/pgmj/easyRasch2/issues
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, knitr, mirt, psychotools (>= 0.7-3),
        stats, utils, rlang
Suggests: difR, eRm, geomtextpath, ggdist, ggtext, iarm, mirai, ggplot2
        (>= 3.4.0), partykit, psychotree, stablelearner, testthat (>=
        3.0.0), rmarkdown, patchwork, scales, mice, ggrepel, lavaan,
        withr
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: cmake make libuv1-dev libx11-dev
Repository: https://pgmj.r-universe.dev
Date/Publication: 2026-10-06 10:49:51 UTC
RemoteUrl: https://github.com/pgmj/easyrasch2
RemoteRef: HEAD
RemoteSha: b45f3a39d9be7a3a6a2bfe9e62708353c6bf9440
NeedsCompilation: no
Packaged: 2026-10-07 08:52:39 UTC; root
Author: Magnus Johansson [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-1669-592X>),
  Nicklas Korsell [ctb] (PCM simulation code),
  Mirka Henninger [ctb] (ORCID: <https://orcid.org/0000-0003-4676-2361>,
    MH / partial-gamma effect-size and ETS-classification algorithms in
    dif_tree.R, adapted under MIT licence from the raschtreeMH and
    effecttree packages),
  Jan Radek [ctb] (ORCID: <https://orcid.org/0009-0003-8842-9206>,
    partial-gamma effect-size and ETS-classification algorithms in
    dif_tree.R, adapted under MIT licence from the effecttree package)
Maintainer: Magnus Johansson <pgmj@pm.me>