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Diferenciamento de Itens em Testes Adaptativos Computadorizados (CAT-DIF)×Teoria de Resposta ao Item (TRI)×
ÁreaPsicometriaPsicometria
FamíliaLatent structureLatent structure
Ano de origem1990s–2000s1952–1968
Autor originalWainer, Zwick, and colleagues in the CAT and DIF literaturesFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
TipoItem bias detection in adaptive testingProbabilistic measurement model
Fonte seminalZwick, R., Thayer, D. T., & Mazzeo, J. (1997). Describing and categorizing DIF in polytomous items. Journal of Educational Measurement, 34(4), 261–285. DOI ↗Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
Outros nomesCAT DIF analysis, adaptive test DIF, DIF in computerized adaptive testing, CAT item bias detectionIRT, latent trait theory, item characteristic curve theory, modern test theory
Relacionados65
ResumoCAT-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.
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ScholarGateComparar métodos: CAT-DIF · Item Response Theory. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare