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Multifaktoriell analys×Partial Least Squares Structural Equation Modeling×
ÄmnesområdePsykometriPsykometri
FamiljLatent structureLatent structure
Ursprungsår19851985
UpphovspersonBrigitte Escofier, Jérôme PagèsHerman Wold
TypMultiblock dimension reductionComponent-based structural equation model
UrsprungskällaEscofier, B., & Pagès, J. (1985). Analyses factorielles simples et multiples : Objectifs, méthodes et interprétation. Dunod. ISBN: 9782040116835Hair, 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
AliasMFA, MFA multiplePLS-SEM, PLS path modeling
Närliggande55
SammanfattningMultiple 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.
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ScholarGateJämför metoder: Multiple Factor Analysis · Partial Least Squares Structural Equation Modeling. Hämtad 2026-06-15 från https://scholargate.app/sv/compare