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Testing Measurement Invariance In Multilevel Data With Unequal Cross-Level Factor Structures, Lihua Yang
Testing Measurement Invariance In Multilevel Data With Unequal Cross-Level Factor Structures, Lihua Yang
Graduate Theses and Dissertations
The test of measurement invariance (MI) investigates whether observed items measure a construct in the same way across different groups or over times. Examining MI is a prerequisite for multiple group comparisons in psychological tests (Schmitt & Kuljanin, 2008). With the prevalence of multilevel data in educational research (e.g., students nested within schools), establishing MI across multiple groups or waves of nested data has brought increasing attention. Two popular techniques for the test of multilevel MI include the multiple-group multilevel confirmatory factor analysis (MMCFA) and the design-based approaches. The MMCFA approach estimates sample covariance matrices at different levels separately. The …