Comparer des méthodes

	Modélisation par équations structurelles par moindres carrés partiels	Modélisation Exploratoire par Équations Structurelles
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1985	2009
Auteur d'origine	Herman Wold	Tihomir Asparouhov, Bengt Muthén
Type	Component-based structural equation model	Hybrid exploratory-confirmatory factor modeling
Source fondatrice	Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445	Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438.
Alias	PLS-SEM, PLS path modeling	ESEM
Apparentées	5	5
Résumé	PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data.	Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load on all factors, which can reveal cross-factor complexity and improve model fit while retaining the ability to test substantive structural theories.