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| Potwierdzająca Analiza Czynnikowa dla Danych Politomicznych× | Teoria odpowiedzi na pozycje (IRT)× | |
|---|---|---|
| Dziedzina | Psychometria | Psychometria |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1984 | 1952–1968 |
| Twórca≠ | Bengt Muthen | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Latent variable / confirmatory measurement model | Probabilistic measurement model |
| Źródło pierwotne≠ | Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Inne nazwy | CFA for ordered categories, ordinal CFA, categorical CFA, WLSMV-CFA | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | Polytomous confirmatory factor analysis (CFA) tests a pre-specified factor structure when items have three or more ordered response categories (e.g., Likert scales). By working with polychoric correlations and robust estimators such as WLSMV, it avoids the distortions that arise when ordered categorical data are treated as continuous. | 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. |
| ScholarGateZbiór danych ↗ |
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