Latent structureScale / measurement
Multi-Group Confirmatory Factor Analysis (MG-CFA)
Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified.
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Sources
- Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI: 10.1177/109442810031002 ↗
- Millsap, R. E. (2011). Statistical Approaches to Measurement Equivalence. Routledge. ISBN: 978-0805859447
Related methods
Referenced by
Bayesian Measurement InvarianceDifferential Item FunctioningMulti-group convergent validityMulti-group Cronbach's alphaMulti-group Differential Item FunctioningMulti-group discriminant validityMulti-group EFAMulti-group Generalizability TheoryMulti-group item analysisMulti-group item response theoryMulti-group McDonald's omegaMulti-group measurement invarianceMulti-group Rasch modelMulti-group Reliability AnalysisMulti-group scale developmentMulti-group test-retest reliabilityOrdinal Measurement InvariancePolytomous Measurement Invariance