Comparer des méthodes

	Tests de l'invariance de mesure robustes	Test d'invariance de mesure
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1994	2000
Auteur d'origine	Albert Satorra & Peter M. Bentler	Vandenberg & Lance
Type	Measurement invariance test with robust corrections	Multi-group confirmatory factor analysis procedure
Source fondatrice	Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage.	Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature. Organizational Research Methods, 3(1), 4–70.
Alias	robust MI testing, robust measurement equivalence, non-normal measurement invariance, robust multi-group CFA invariance	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Apparentées	3	3
Résumé	Robust measurement invariance testing evaluates whether a psychometric instrument measures the same latent construct in the same way across groups when observed data violate multivariate normality. It adapts standard multi-group CFA sequences by replacing ordinary chi-square statistics with robust alternatives such as the Satorra-Bentler scaled statistic, yielding trustworthy conclusions about factor loadings, intercepts, and residual variances even with skewed or ordinal data.	Measurement invariance testing is a sequence of nested confirmatory factor analysis (CFA) models that examines whether a psychological scale measures the same latent construct in the same way across distinct groups or time points. Systematized and popularized by Vandenberg and Lance (2000), the procedure tests a hierarchy of constraints — from identical factor patterns to identical item intercepts — so that researchers can justify meaningful group comparisons on latent means.