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
NeedsCompilation: no
Packaged: 2026-04-20 20:43:11 UTC; Subir
Author: Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-21 20:52:36 UTC
