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| Phân tích Độ tương đồng Chức năng Mục (Ordinal DIF)× | Lý thuyết Ứng đáp Câu hỏi (IRT)× | |
|---|---|---|
| Lĩnh vực | Trắc lượng tâm lý | Trắc lượng tâm lý |
| Họ | Latent structure | Latent structure |
| Năm ra đời≠ | 1999-2001 | 1952–1968 |
| Người khởi xướng≠ | Zumbo (logistic extension) and Penfield (Mantel generalization) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Loại≠ | Item bias detection for ordered-category items | Probabilistic measurement model |
| Công trình gốc≠ | Zumbo, B. D. (1999). A handbook on the theory and methods of differential item functioning (DIF): Logistic regression modeling as a unitary framework for binary and Likert-type (ordinal) item scores. Ottawa: Directorate of Human Resources Research and Evaluation, Department of National Defense. link ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Tên gọi khác | ordinal DIF, polytomous DIF, DIF for ordered categories, ordinal logistic DIF | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Liên quan≠ | 6 | 5 |
| Tóm tắt≠ | Ordinal differential item functioning analysis detects whether an ordered-category item (such as a Likert-scale question) functions differently across demographic or cultural groups after controlling for the latent trait being measured. It extends classical binary DIF methods to polytomous response formats common in psychological and educational scales. | 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. |
| ScholarGateBộ dữ liệu ↗ |
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