Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Порядковый конфирматорный факторный анализ× | Теория отклика на задания (IRT)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1984 | 1952–1968 |
| Автор метода≠ | Bengt O. Muthén | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Тип≠ | Latent variable / structural | Probabilistic measurement model |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Связанные | 5 | 5 |
| Сводка≠ | Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses 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. |
| ScholarGateНабор данных ↗ |
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