Compară metode

	Funcționare diferențială a itemilor politomi (Polytomous DIF)	Analiza factoriala confirmatorie (CFA)
Domeniu	Psihometrie	Psihometrie
Familie	Latent structure	Latent structure
Anul apariției	1990s–2000s	1969
Autorul original	Bruno D. Zumbo and colleagues (ordinal logistic regression framework); Robert D. Ankenmann, Hariharan Swaminathan and others (IRT-based extensions)	Karl Gustav Jöreskog
Tip	Measurement fairness / item bias detection	Hypothesis-testing latent variable model
Sursa seminală	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.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Denumiri alternative	Polytomous DIF, DIF for polytomous items, ordinal DIF analysis, graded-response DIF	CFA, confirmatory FA, measurement model, restricted factor analysis
Înrudite	4	4
Rezumat	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.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.