Methoden vergelijken

	Betrouwbaarheid bij Herhaalde Meting in Meerdere Groepen	Multi-Group Confirmatory Factor Analysis (MG-CFA)
Vakgebied	Psychometrie	Psychometrie
Familie	Latent structure	Latent structure
Jaar van ontstaan	1979–2000	1971
Grondlegger	Systematic multi-group extensions developed alongside measurement invariance frameworks (Vandenberg & Lance, 2000); intraclass correlation foundation in Shrout & Fleiss (1979)	Karl Jöreskog
Type	Reliability estimation across groups	Measurement model / invariance test
Oorspronkelijke bron	Shrout, P. E. & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428.	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.
Aliassen	multi-group temporal stability, cross-group test-retest reliability, group-comparative retest reliability, multi-sample temporal consistency	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Verwant	5	6
Samenvatting	Multi-group test-retest reliability evaluates whether a measure produces stable scores across time separately for two or more defined groups — such as different genders, age cohorts, or clinical populations — and determines whether the degree of that temporal stability is equivalent across those groups.	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.