Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Analýza více faktorů× | Parciální metoda nejmenších čtverců v modelování pomocí strukturálních rovnic× | |
|---|---|---|
| Obor | Psychometrika | Psychometrika |
| Rodina | Latent structure | Latent structure |
| Rok vzniku | 1985 | 1985 |
| Tvůrce≠ | Brigitte Escofier, Jérôme Pagès | Herman Wold |
| Typ≠ | Multiblock dimension reduction | Component-based structural equation model |
| Původní zdroj≠ | 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 |
| Další názvy | MFA, MFA multiple | PLS-SEM, PLS path modeling |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | 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. |
| ScholarGateDatová sada ↗ |
|
|