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Linganisha mbinu

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Uchanganuzi wa Hisabati wa Viwango Vilivyopunguzwa vya Sehemu (PLS-SEM)×Fuzzy ANOVA×
NyanjaSaikometrikiSaikometriki
FamiliaLatent structureLatent structure
Mwaka wa asili19852011
MwanzilishiHerman WoldReinhard Viertl
AinaComponent-based structural equation modelAnalysis of variance for fuzzy data
Chanzo asiliaHair, 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: 9781483377445Viertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802
Majina mbadalaPLS-SEM, PLS path modeling
Zinazohusiana54
MuhtasariPLS-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.
ScholarGateSeti ya data
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  1. v1
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  3. PUBLISHED

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