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| Partial Least Squares Strukturgleichungsmodellierung× | Fuzzy ANOVA× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1985 | 2011 |
| Urheber≠ | Herman Wold | Reinhard Viertl |
| Typ≠ | Component-based structural equation model | Analysis of variance for fuzzy data |
| Wegweisende Quelle≠ | 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 | Viertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802 |
| Aliasnamen≠ | PLS-SEM, PLS path modeling | — |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | 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. | Fuzzy ANOVA extends classical analysis of variance to fuzzy data where observations and group memberships are imprecise or uncertain. Developed by Viertl and others, Fuzzy ANOVA tests whether fuzzy-valued groups differ significantly while accounting for inherent measurement uncertainty. |
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