Package: easyRasch2
Title: Psychometric Analysis with Rasch Measurement Theory
Version: 1.1.1
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,
    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
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, 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
NeedsCompilation: no
Packaged: 2026-08-04 16:34:46 UTC; magnus.johansson.3
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>
Repository: CRAN
Date/Publication: 2026-08-04 18:00:15 UTC
Built: R 4.6.1; ; 2026-08-19 15:22:05 UTC; windows
