Σύγκριση μεθόδων

	Συγκλίνουσα Εγκυρότητα για Ηλεκτρονικά Προσαρμοστικά Τεστ	Θεωρία Απόκρισης Ερωτήσεων (IRT)
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	1989–2000	1952–1968
Δημιουργός	Samuel Messick (validity framework); Wainer and colleagues (CAT context)	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Τύπος	Validity evidence / construct validation	Probabilistic measurement model
Θεμελιώδης πηγή	Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Εναλλακτικές ονομασίες	CAT convergent validity, adaptive test construct validation, CAT validity evidence, convergent validity in CAT	IRT, latent trait theory, item characteristic curve theory, modern test theory
Συναφείς	5	5
Σύνοψη	Convergent validity assessment for computerized adaptive tests (CATs) examines whether the ability or trait estimates produced by an adaptive algorithm correlate substantially with scores from other measures of the same construct. Because each examinee receives a different subset of items in a CAT, demonstrating that the resulting scores still converge with theoretically related external measures is a critical step in establishing construct validity evidence.	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.