Võrdle meetodeid

	Polütoomne diferentseeritud üksuse funktsioneerimine (Polütoomne DIF)	Item Response Theory (IRT)
Valdkond	Psühhomeetria	Psühhomeetria
Perekond	Latent structure	Latent structure
Tekkeaasta	1990s–2000s	1952–1968
Looja	Bruno D. Zumbo and colleagues (ordinal logistic regression framework); Robert D. Ankenmann, Hariharan Swaminathan and others (IRT-based extensions)	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Tüüp	Measurement fairness / item bias detection	Probabilistic measurement model
Algallikas	Zumbo, B. D. (1999). A handbook on the theory and methods of differential item functioning (DIF): Logistic regression modeling as a unitary framework for binary and Likert-type (ordinal) item scores. Directorate of Human Resources Research and Evaluation, Department of National Defense.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Rööpnimetused	Polytomous DIF, DIF for polytomous items, ordinal DIF analysis, graded-response DIF	IRT, latent trait theory, item characteristic curve theory, modern test theory
Seotud	4	5
Kokkuvõte	Polytomous differential item functioning detects whether a test or survey item with more than two ordered response categories (e.g., Likert-type scales, partial-credit items) functions differently across groups such as gender, ethnicity, or language background, after controlling for the latent trait being measured. It extends classical binary DIF methods to ordinal response formats.	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.