Comparer des méthodes

	Analyse Multi-Factorielle	Modélisation par équations structurelles par moindres carrés partiels
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1985	1985
Auteur d'origine	Brigitte Escofier, Jérôme Pagès	Herman Wold
Type	Multiblock dimension reduction	Component-based structural equation model
Source fondatrice	Escofier, B., & Pagès, J. (1985). Analyses factorielles simples et multiples : Objectifs, méthodes et interprétation. Dunod. ISBN: 9782040116835	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
Alias	MFA, MFA multiple	PLS-SEM, PLS path modeling
Apparentées	5	5
Résumé	Multiple Factor Analysis (MFA) is a dimension reduction technique developed by Escofier and Pagès (1985) for analyzing multiple groups of variables measured on the same observations. MFA balances the influence of each variable group to provide a unified view of how observations relate across multiple perspectives.	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.