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| Bifaktormodell (allgemeine und spezifische Faktoren)× | Item Response Theory (IRT)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1937 | 1952–1968 |
| Urheber≠ | Holzinger & Swineford (1937); modern revival by Reise (2012) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Confirmatory latent variable model | Probabilistic measurement model |
| Wegweisende Quelle≠ | Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Aliasnamen | Bifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score. | 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. |
| ScholarGateDatensatz ↗ |
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