Порівняння методів

	Багаторівневе диференційне функціонування елементів (Multilevel DIF)	Тестування інваріантності вимірювання
Галузь	Психометрія	Психометрія
Родина	Latent structure	Latent structure
Рік появи	2001	2000
Автор методу	Kamata (2001) and subsequent multilevel IRT/DIF literature	Vandenberg & Lance
Тип	Bias detection / multilevel measurement model	Multi-group confirmatory factor analysis procedure
Основоположне джерело	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.
Інші назви	multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Пов'язані	5	3
Підсумок	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.