Comparer des méthodes

	Théorie de la généralisabilité appliquée aux tests adaptatifs informatisés	Théorie de la réponse aux items (TRI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1972 (G-theory); CAT application 1990s–2000s	1952–1968
Auteur d'origine	Lee J. Cronbach (G-theory); applied to CAT by Brennan and others	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Reliability / generalizability analysis	Probabilistic measurement model
Source fondatrice	Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Alias	CAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysis	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	6	5
Résumé	Generalizability theory (G-theory) applied to computerized adaptive testing (CAT) evaluates the dependability of adaptive test scores by decomposing score variance across measurement facets such as persons, items, and occasions. Unlike classical test theory, G-theory quantifies multiple simultaneous sources of measurement error, offering a richer reliability picture for adaptively administered assessments.	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.