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| Fuzzy ANOVA× | Osittaisella pienimmän neliösumman rakenneyhtälömallinnus (PLS-SEM)× | |
|---|---|---|
| Tieteenala | Psykometriikka | Psykometriikka |
| Menetelmäperhe | Latent structure | Latent structure |
| Syntyvuosi≠ | 2011 | 1985 |
| Kehittäjä≠ | Reinhard Viertl | Herman Wold |
| Tyyppi≠ | Analysis of variance for fuzzy data | Component-based structural equation model |
| Alkuperäislähde≠ | Viertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802 | 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 |
| Rinnakkaisnimet≠ | — | PLS-SEM, PLS path modeling |
| Liittyvät≠ | 4 | 5 |
| Tiivistelmä≠ | 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. | 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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