Compară metode

	Analiza funcționării diferențiate a itemilor multinivel (Multilevel DIF)	Testarea Invarianței Măsurării
Domeniu	Psihometrie	Psihometrie
Familie	Latent structure	Latent structure
Anul apariției	2001	2000
Autorul original	Kamata (2001) and subsequent multilevel IRT/DIF literature	Vandenberg & Lance
Tip	Bias detection / multilevel measurement model	Multi-group confirmatory factor analysis procedure
Sursa seminală	French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 96–113.	Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature. Organizational Research Methods, 3(1), 4–70.
Denumiri alternative	multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Înrudite	5	3
Rezumat	Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuine item bias from artificial DIF signals caused by ignoring clustering.	Measurement invariance testing is a sequence of nested confirmatory factor analysis (CFA) models that examines whether a psychological scale measures the same latent construct in the same way across distinct groups or time points. Systematized and popularized by Vandenberg and Lance (2000), the procedure tests a hierarchy of constraints — from identical factor patterns to identical item intercepts — so that researchers can justify meaningful group comparisons on latent means.