Comparer des méthodes

	Modélisation par équations structurelles (MES)	Analyse Factorielle Confirmatoire (AFC)
Domaine	Statistique	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1970	1969
Auteur d'origine	Karl Jöreskog (LISREL framework, 1970s)	Karl Gustav Jöreskog
Type	Latent variable / causal modeling	Hypothesis-testing latent variable model
Source fondatrice	Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	5	4
Résumé	Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.