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Multipel faktoranalyse×Fuzzy ANOVA×
FagområdePsykometriPsykometri
FamilieLatent structureLatent structure
Oprindelsesår19852011
OphavspersonBrigitte Escofier, Jérôme PagèsReinhard Viertl
TypeMultiblock dimension reductionAnalysis of variance for fuzzy data
Oprindelig kildeEscofier, B., & Pagès, J. (1985). Analyses factorielles simples et multiples : Objectifs, méthodes et interprétation. Dunod. ISBN: 9782040116835Viertl, R. (2011). Statistical Methods for Fuzzy Data. Wiley. ISBN: 9780470664802
AliasserMFA, MFA multiple
Relaterede54
ResuméMultiple Factor Analysis (MFA) is a dimension reduction technique developed by Escofier and Pagès (1985) for analyzing multiple groups of variables measured on the same observations. MFA balances the influence of each variable group to provide a unified view of how observations relate across multiple perspectives.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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ScholarGateSammenlign metoder: Multiple Factor Analysis · Fuzzy ANOVA. Hentet 2026-06-15 fra https://scholargate.app/da/compare