手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| コンピュータ適応型テスト項目機能差 (CAT-DIF)× | 項目応答理論 (IRT)× | |
|---|---|---|
| 分野 | 心理測定学 | 心理測定学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 1990s–2000s | 1952–1968 |
| 提唱者≠ | Wainer, Zwick, and colleagues in the CAT and DIF literatures | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 種類≠ | Item bias detection in adaptive testing | Probabilistic measurement model |
| 原典≠ | Zwick, R., Thayer, D. T., & Mazzeo, J. (1997). Describing and categorizing DIF in polytomous items. Journal of Educational Measurement, 34(4), 261–285. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 別名 | CAT DIF analysis, adaptive test DIF, DIF in computerized adaptive testing, CAT item bias detection | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 関連≠ | 6 | 5 |
| 概要≠ | CAT-DIF identifies items in a computerized adaptive test that behave differently across demographic or group subpopulations after controlling for overall ability. Because adaptive algorithms select items non-randomly based on each examinee's estimated proficiency, standard DIF detection methods require adjustment before they can be validly applied in this context. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGateデータセット ↗ |
|
|