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| Eksploracyjna analiza czynnikowa dla danych politomicznych× | Teoria odpowiedzi na pozycje (IRT)× | |
|---|---|---|
| Dziedzina | Psychometria | Psychometria |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1978 | 1952–1968 |
| Twórca≠ | Bengt Muthén | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Latent variable / dimension reduction | 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 | EFA for ordered-categorical data, polychoric EFA, ordinal exploratory factor analysis, polytomous factor analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | Polytomous exploratory factor analysis extends standard EFA to ordered categorical (Likert-type) response data by replacing the Pearson correlation matrix with a polychoric correlation matrix. It recovers the latent continuous variable that each polytomous item is assumed to reflect, yielding more accurate factor loadings and better-defined factor structures than treating ordinal scores as if they were 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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