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| Generalisierbarkeitstheorie (G-Theorie)× | Item Response Theory (IRT)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1963–1972 | 1952–1968 |
| Urheber≠ | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Variance-components reliability model | Probabilistic measurement model |
| Wegweisende Quelle≠ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Aliasnamen≠ | G-theory, G-study / D-study framework, variance components reliability | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Verwandt≠ | 4 | 5 |
| Zusammenfassung≠ | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. | 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. |
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