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Test de Friedman robuste×ANOVA à mesures répétées×
DomaineStatistiqueStatistique
FamilleHypothesis testHypothesis test
Année d'origine1990s–2000s1992
Auteur d'origineExtension of Friedman (1937); robust variants developed by Wilcox and colleaguesGirden (textbook treatment); Field (2013)
TypeRobust nonparametric repeated measures comparisonParametric within-subjects mean comparison
Source fondatriceWilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185
Aliasrobust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust testwithin-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA
Apparentées64
RésuméThe robust Friedman test is a nonparametric procedure for comparing three or more related (within-subjects) conditions that replaces standard ranking or mean-based summaries with robust location estimates — typically trimmed means or Winsorized statistics — to reduce the influence of outliers and heavy-tailed distributions on the inference.Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013).
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ScholarGateComparer des méthodes: Robust Friedman test · Repeated-measures ANOVA. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare