Comparer des méthodes

	Modélisation par équations structurelles robuste	Modélisation par équations structurelles
Domaine	Statistique	Statistiques de recherche
Famille	Latent structure	Process / pipeline
Année d'origine	1994	1921
Auteur d'origine	Albert Satorra & Peter M. Bentler	Sewall Wright
Type	Latent variable / path model with robust inference	Method
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 (pp. 399–419). Sage.	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.
Alias	Robust SEM, SEM with robust standard errors, Satorra-Bentler SEM, non-normal SEM	SEM, path analysis, latent variable modeling, causal modeling
Apparentées	5	3
Résumé	Robust structural equation modeling (Robust SEM) applies the full SEM framework — simultaneous estimation of measurement and structural relations among latent variables — while using corrected test statistics and sandwich standard errors that remain valid when observed data depart from multivariate normality. The Satorra-Bentler scaled chi-square is the most widely used correction.	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.