Methoden vergelijken

	Multilevel Differential Item Functioning (Multilevel DIF)	Testen van Meetinvariantie
Vakgebied	Psychometrie	Psychometrie
Familie	Latent structure	Latent structure
Jaar van ontstaan	2001	2000
Grondlegger	Kamata (2001) and subsequent multilevel IRT/DIF literature	Vandenberg & Lance
Type	Bias detection / multilevel measurement model	Multi-group confirmatory factor analysis procedure
Oorspronkelijke bron	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.
Aliassen	multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Verwant	5	3
Samenvatting	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.