Comparer des méthodes

	Analyse Factorielle Confirmatoire (AFC)	Modélisation par équations structurelles (MES)
Domaine	Psychométrie	Statistique
Famille	Latent structure	Latent structure
Année d'origine	1969	1970
Auteur d'origine	Karl Gustav Jöreskog	Karl Jöreskog (LISREL framework, 1970s)
Type	Hypothesis-testing latent variable model	Latent variable / causal modeling
Source fondatrice	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.	Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Alias	CFA, confirmatory FA, measurement model, restricted factor analysis	Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Apparentées	4	5
Résumé	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.	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.