Package: aiDIF
Type: Package
Title: Differential Item Functioning for AI-Scored Assessments
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: Detects and quantifies differential item functioning (DIF)
        in AI-scored educational and psychological assessments.
        Provides a fully self-contained robust DIF engine (M-estimation
        via iteratively re-weighted least squares with the bi-square
        loss) alongside the novel Differential AI Scoring Bias (DASB)
        test, which detects item-level scoring shifts that differ
        across subgroups when comparing human and AI scoring
        conditions. Includes simulation utilities, anchor weight
        diagnostics, and an AI-effect classification framework.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Matrix, stats, graphics
Suggests: mirt, testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
RoxygenNote: 7.3.3
VignetteBuilder: knitr
URL: https://github.com/causalfragility-lab/aiDIF
BugReports: https://github.com/causalfragility-lab/aiDIF/issues
Repository: https://causalfragility-lab.r-universe.dev
Date/Publication: 2026-04-20 20:41:21 UTC
RemoteUrl: https://github.com/causalfragility-lab/aidif
RemoteRef: HEAD
RemoteSha: 9515141f1926b004aa6636f9fafafb8781fd19f8
NeedsCompilation: no
Packaged: 2026-07-21 08:47:12 UTC; root
Author: Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>