Comparer des méthodes

	Théorie de la généralisabilité (Théorie G)	Théorie de la réponse aux items (TRI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1963–1972	1952–1968
Auteur d'origine	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Variance-components reliability model	Probabilistic measurement model
Source fondatrice	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Alias	G-theory, G-study / D-study framework, variance components reliability	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	4	5
Résumé	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.