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| Bayesian Scale Development× | Item Response Theory (IRT)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1990s–2000s | 1952–1968 |
| Urheber≠ | Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Typ≠ | Bayesian probabilistic scale construction | Probabilistic measurement model |
| Wegweisende Quelle≠ | De Ayala, R. J. (2009). The Theory and Practice of Item Response Theory. Guilford Press. ISBN: 978-1593858698 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Aliasnamen | Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | Bayesian scale development applies Bayesian statistical inference to the construction and evaluation of psychometric scales. Rather than relying on single point estimates of item and person parameters, it produces full posterior distributions that quantify uncertainty, incorporate prior knowledge, and support principled decisions about item retention, reliability, and validity in small or complex samples. | 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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