Comparer des méthodes

	Multilevel Item Response Theory	Théorie de la réponse aux items (TRI)
Domaine	Education	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	2010	1952–1968
Auteur d'origine	Adams, Wilson & Wu; Fox & Glas; De Boeck & Wilson	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Item response models with a multilevel structure on the latent ability	Probabilistic measurement model
Source fondatrice	Fox, J.-P. (2010). Bayesian Item Response Modeling: Theory and Applications. Springer.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Alias	Multilevel IRT, MLIRT, Hierarchical IRT, Explanatory Item Response Models	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	4	5
Résumé	Multilevel item response theory (MLIRT) joins two powerful frameworks: an IRT measurement model that turns item responses into a latent ability, and a multilevel structural model that explains how that ability varies across nested groups such as classrooms, schools, or countries. Instead of first scoring a test and then running a multilevel regression on the scores, MLIRT does both at once, so that measurement error in ability is properly carried into the group-level analysis. It is the rigorous way to study how student and school characteristics relate to a latent trait measured by a test.	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.