Methoden vergelijken

	Multi-Group Confirmatory Factor Analysis (MG-CFA)	Structurele vergelijkingsmodellering
Vakgebied	Psychometrie	Onderzoeksstatistiek
Familie	Latent structure	Process / pipeline
Jaar van ontstaan	1971	1921
Grondlegger	Karl Jöreskog	Sewall Wright
Type	Measurement model / invariance test	Method
Oorspronkelijke bron	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.	Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm.
Aliassen	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA	SEM, path analysis, latent variable modeling, causal modeling
Verwant	6	3
Samenvatting	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.	Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis.