विधियों की तुलना करें

	बहुकारक विश्लेषण	आंशिक न्यूनतम वर्ग संरचनात्मक समीकरण मॉडलिंग
क्षेत्र	मनोमिति	मनोमिति
परिवार	Latent structure	Latent structure
उद्भव वर्ष	1985	1985
प्रवर्तक	Brigitte Escofier, Jérôme Pagès	Herman Wold
प्रकार	Multiblock dimension reduction	Component-based structural equation model
मौलिक स्रोत	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
उपनाम	MFA, MFA multiple	PLS-SEM, PLS path modeling
संबंधित	5	5
सारांश	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.