Salīdzināt metodes

	Daudzgrupu konverģentā validitāte	Daudzgrupas apstiprinošā faktoru analīze (MG-CFA)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1981 / 2000	1971
Autors	Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension)	Karl Jöreskog
Tips	Validity assessment procedure	Measurement model / invariance test
Pirmavots	Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.	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.
Citi nosaukumi	cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groups	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Saistītās	6	6
Kopsavilkums	Multi-group convergent validity examines whether items purported to measure the same latent construct relate strongly to that construct consistently across distinct subgroups such as demographic categories, cultures, or experimental conditions. It extends single-sample convergent validity checks into a comparative multi-group confirmatory factor analysis framework.	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.