Methoden vergleichen

	Multiple Faktorenanalyse	Partial Least Squares Strukturgleichungsmodellierung
Fachgebiet	Psychometrie	Psychometrie
Familie	Latent structure	Latent structure
Entstehungsjahr	1985	1985
Urheber	Brigitte Escofier, Jérôme Pagès	Herman Wold
Typ	Multiblock dimension reduction	Component-based structural equation model
Wegweisende Quelle	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
Aliasnamen	MFA, MFA multiple	PLS-SEM, PLS path modeling
Verwandt	5	5
Zusammenfassung	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.