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| Phân tích nhân tố khám phá mạnh mẽ× | 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≠ | 2000–2003 | 1952–1968 |
| Người khởi xướng≠ | Pison, Rousseeuw, Filzmoser, and Croux; Yuan and Bentler (parallel streams) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Loại≠ | Latent variable / dimension reduction (robust) | Probabilistic measurement model |
| Công trình gốc≠ | Yuan, K.-H., & Bentler, P. M. (2000). Robust mean and covariance structure analysis through iteratively reweighted least squares. Psychometrika, 65(1), 43–58. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Tên gọi khác | robust EFA, robust factor analysis, outlier-resistant factor analysis, EFA with robust estimation | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Liên quan≠ | 4 | 5 |
| Tóm tắt≠ | Robust exploratory factor analysis discovers the latent factor structure of a set of items using estimation methods that are resistant to outliers and violations of multivariate normality. It applies the same measurement model as standard EFA but replaces classical covariance estimation with robust counterparts — such as minimum covariance determinant or iteratively reweighted least squares — so that a small fraction of atypical cases cannot distort the recovered factor loadings. | 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. |
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