Comparer des méthodes

	Validité convergente multiniveaux	Test d'invariance de mesure
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	2005	2000
Auteur d'origine	Dyer, Hanges & Hall; Chen, Bliese & Mathieu	Vandenberg & Lance
Type	Measurement validity evaluation	Multi-group confirmatory factor analysis procedure
Source fondatrice	Dyer, N. G., Hanges, P. J. & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167.	Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature. Organizational Research Methods, 3(1), 4–70.
Alias	cross-level convergent validity, multilevel measurement validity, between-level convergent validity	Factorial Invariance, Measurement Equivalence, Configural-Metric-Scalar Testing, Ölçüm Değişmezliği
Apparentées	4	3
Résumé	Multilevel convergent validity evaluates whether items or scales intended to measure the same construct show coherent, strong associations at each level of a nested data structure — within individuals, within groups, and between groups. It extends classical convergent validity from single-level measurement models into the multilevel confirmatory factor analysis (ML-CFA) framework.	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.