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| Testowanie niezmienniczości pomiaru porządkowego× | Teoria odpowiedzi na pozycje (IRT)× | |
|---|---|---|
| Dziedzina | Psychometria | Psychometria |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1984–2011 | 1952–1968 |
| Twórca≠ | Roger Millsap; Bengt Muthén | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Multi-group model comparison | Probabilistic measurement model |
| Źródło pierwotne≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Inne nazwy | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal 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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