Comparer des méthodes

	CAT-DIF	Théorie de la réponse aux items (TRI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1990s–2000s	1952–1968
Auteur d'origine	Wainer, Zwick, and colleagues in the CAT and DIF literatures	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Item bias detection in adaptive testing	Probabilistic measurement model
Source fondatrice	Zwick, R., Thayer, D. T., & Mazzeo, J. (1997). Describing and categorizing DIF in polytomous items. Journal of Educational Measurement, 34(4), 261–285.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Alias	CAT DIF analysis, adaptive test DIF, DIF in computerized adaptive testing, CAT item bias detection	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	6	5
Résumé	CAT-DIF identifies items in a computerized adaptive test that behave differently across demographic or group subpopulations after controlling for overall ability. Because adaptive algorithms select items non-randomly based on each examinee's estimated proficiency, standard DIF detection methods require adjustment before they can be validly applied in this context.	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.