Background | The Example Dataset | Fitting the Model | Full Report | The DASB Test | AI-Effect Classification | Visualisations | Simulation | References
Package: aiDIF 0.1.0
aiDIF: Differential Item Functioning for AI-Scored Assessments
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.
Authors:
aiDIF_0.1.0.tar.gz
aiDIF_0.1.0.zip(r-4.7-any)aiDIF_0.1.0.zip(r-4.6-any)aiDIF_0.1.0.zip(r-4.5-any)
aiDIF_0.1.0.tgz(r-4.6-any)aiDIF_0.1.0.tgz(r-4.5-any)
aiDIF_0.1.0.tar.gz(r-4.7-any)aiDIF_0.1.0.tar.gz(r-4.6-any)
aiDIF_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
aiDIF/json (API)
| # Install 'aiDIF' in R: |
| install.packages('aiDIF', repos = c('https://causalfragility-lab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/causalfragility-lab/aidif/issues
Last updated from:9515141f19. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 152 | ||
| source / vignettes | OK | 180 | ||
| linux-release-x86_64 | OK | 146 | ||
| macos-release-arm64 | OK | 82 | ||
| macos-oldrel-arm64 | OK | 156 | ||
| windows-devel | OK | 147 | ||
| windows-release | OK | 105 | ||
| windows-oldrel | OK | 107 | ||
| wasm-release | OK | 120 |
Exports:ai_effect_summaryanchor_weightsestimate_robust_scalefit_aidifmake_aidif_egread_ai_scoredscoring_bias_testsimulate_aidif_data
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Summarise the effect of AI scoring on DIF flagging. | ai_effect_summary |
| Anchor item weights from the robust AI-DIF procedure. | anchor_weights |
| Robust DIF scale estimation via IRLS | estimate_robust_scale |
| Fit the AI-DIF model | fit_aidif |
| Built-in example dataset for aiDIF | make_aidif_eg |
| S3 plot method for class '"aidif"'. | plot.aidif |
| S3 print method for class '"aidif"'. | print.aidif |
| Validate and bundle paired human/AI parameter estimates | read_ai_scored |
| Differential AI Scoring Bias (DASB) test. | scoring_bias_test |
| Simulate item parameter estimates for the AI-DIF model. | simulate_aidif_data |
| S3 summary method for class '"aidif"'. | summary.aidif |
