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Fuzzy ANOVA×Uchanganuzi wa Hisabati wa Viwango Vilivyopunguzwa vya Sehemu (PLS-SEM)×
NyanjaSaikometrikiSaikometriki
FamiliaLatent structureLatent structure
Mwaka wa asili20111985
MwanzilishiReinhard ViertlHerman Wold
AinaAnalysis of variance for fuzzy dataComponent-based structural equation model
Chanzo asiliaViertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802Hair, 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
Majina mbadalaPLS-SEM, PLS path modeling
Zinazohusiana45
MuhtasariFuzzy 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.
ScholarGateSeti ya data
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  1. v1
  2. 3 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Fuzzy ANOVA · Partial Least Squares Structural Equation Modeling. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare