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Pemodelan Persamaan Struktural Kuasa Dua Separa×ANOVA Kabur×
BidangPsikometrikPsikometrik
KeluargaLatent structureLatent structure
Tahun asal19852011
PengasasHerman WoldReinhard Viertl
JenisComponent-based structural equation modelAnalysis of variance for fuzzy data
Sumber perintisHair, 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
AliasPLS-SEM, PLS path modeling
Berkaitan54
RingkasanPLS-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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ScholarGateBandingkan kaedah: Partial Least Squares Structural Equation Modeling · Fuzzy ANOVA. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare