Σύγκριση μεθόδων

	Ανάλυση Διαφορικής Λειτουργίας Αντικειμένων σε Πολλαπλά Επίπεδα (Multilevel DIF)	Έλεγχος Αναλλοιότητας Μετρήσεων
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	2001	2000
Δημιουργός	Kamata (2001) and subsequent multilevel IRT/DIF literature	Vandenberg & Lance
Τύπος	Bias detection / multilevel measurement model	Multi-group confirmatory factor analysis procedure
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Συναφείς	5	3
Σύνοψη	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.