Package: aiEvalR
Type: Package
Title: Statistical and Psychometric Evaluation of AI Systems
Version: 0.1.0
Authors@R: person("Subir", "Hait", email = "haitsubi@msu.edu",
    role = c("aut", "cre"), comment = c(ORCID = "0009-0004-9871-9677"))
Description: Evaluates artificial intelligence (AI) systems as
        measurement instruments using psychometric methods. Provides
        multi-facet generalizability theory (G-study and D-study) via
        'lme4', reliability via the intraclass correlation coefficient
        (ICC), calibration via the expected calibration error (ECE) and
        Brier score, robustness stress testing, and group disparity
        diagnostics. Item-level differential item functioning (DIF)
        based on item response theory (IRT) is delegated to the 'aiDIF'
        package. Methods follow Cronbach, Gleser, Nanda and Rajaratnam
        (1972, <ISBN:9780471188506>) and Brennan (2001)
        <doi:10.1007/978-1-4757-3456-0>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
Depends: R (>= 4.1.0)
Imports: stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr, boot, lme4,
        dplyr, ggplot2, aiDIF, spelling
Config/testthat/edition: 3
URL: https://github.com/causalfragility-lab/aiEvalR
BugReports: https://github.com/causalfragility-lab/aiEvalR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-20 09:21:37 UTC; root
Author: Subir Hait [aut, cre] (<https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>
Config/roxygen2/version: 8.0.0
Repository: https://subirhait.r-universe.dev
Date/Publication: 2026-08-06 20:25:11 UTC
RemoteUrl: https://github.com/subirhait/aievalr
RemoteRef: HEAD
RemoteSha: 79c93e72ed8db61a7a8a91ce4d2cb6e19bfb9b52