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  "Title": "Differential Item Functioning for AI-Scored Assessments",
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  "Description": "Detects and quantifies differential item functioning (DIF)\nin AI-scored educational and psychological assessments.\nProvides a fully self-contained robust DIF engine (M-estimation\nvia iteratively re-weighted least squares with the bi-square\nloss) alongside the Differential AI Scoring Bias (DASB) test,\nwhich detects item-level scoring shifts that differ across\nsubgroups when comparing human and AI scoring conditions.\nSupports independent and paired scoring designs, robust linking\nof the cross-condition contrast, multiplicity control,\nconversion of fitted 'mirt' models to package inputs,\nsimulation utilities, anchor weight diagnostics, and an\nAI-effect classification framework. Methods follow Halpin\n(2024) <doi:10.1007/s11336-024-09957-6>.",
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  "Encoding": "UTF-8",
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  "Repository": "https://subirhait.r-universe.dev",
  "Date/Publication": "2026-09-04 16:13:07 UTC",
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  "Author": "Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)",
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      "page": "ai_effect_summary",
      "title": "Summarise the effect of AI scoring on DIF flagging",
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    },
    {
      "page": "anchor_weights",
      "title": "Anchor item weights from the robust AI-DIF procedure",
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        "anchor_weights"
      ]
    },
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      "page": "as_aidif",
      "title": "Convert a fitted IRT model into aiDIF input",
      "topics": [
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        "as_aidif.MultipleGroupClass"
      ]
    },
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      "title": "Robust DIF scale estimation via IRLS",
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        "estimate_robust_scale"
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      "title": "Fit the AI-DIF model",
      "topics": [
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      "title": "Built-in example dataset for aiDIF",
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        "2. Who should use aiDIF",
        "3. The example data",
        "4. Calibration and identification",
        "5. Independent and paired scoring designs",
        "6. Fitting",
        "7. Conventional DIF in each condition",
        "8. DASB, intervals, and multiplicity",
        "9. Describing the pattern of change",
        "10. Anchor diagnostics",
        "11. Visualisation",
        "12. Full report",
        "13. Using aiDIF after calibration with mirt",
        "14. Simulating item-parameter inputs",
        "15. Limitations",
        "References"
      ],
      "created": "2026-04-20 19:10:05",
      "modified": "2026-09-04 15:01:38",
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