Bandingkan metode

	Analisis Faktor Ganda	Pemodelan Persamaan Struktural Partial Least Squares
Bidang	Psikometri	Psikometri
Keluarga	Latent structure	Latent structure
Tahun asal	1985	1985
Pencetus	Brigitte Escofier, Jérôme Pagès	Herman Wold
Tipe	Multiblock dimension reduction	Component-based structural equation model
Sumber perintis	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
Terkait	5	5
Ringkasan	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.