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Analyse de la taille d'effet robuste×Test t robuste pour échantillons indépendants×
DomaineStatistiqueStatistique
FamilleHypothesis testHypothesis test
Année d'origine2005 (formalized)1974–1990s
Auteur d'origineAlgina, Keselman & Penfield; WilcoxRand R. Wilcox; Karen K. Yuen (trimmed-mean form)
TypeRobust effect size estimationRobust parametric mean comparison
Source fondatriceAlgina, J., Keselman, H. J., & Penfield, R. D. (2005). An alternative to Cohen's standardized mean difference effect size: A robust parameter and confidence interval in the two independent groups case. Psychological Methods, 10(3), 317–328. DOI ↗Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
Aliasrobust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean differenceYuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test
Apparentées52
RésuméRobust effect size analysis quantifies the magnitude of a difference or association using estimators that are resistant to outliers and violations of normality. Rather than relying on classical statistics such as Cohen's d based on sample means and standard deviations, robust variants use trimmed means and Winsorized standard deviations to produce effect size estimates that accurately reflect the typical effect rather than being inflated by extreme values.The robust independent samples t-test compares the central tendency of two independent groups using trimmed means and Winsorized variances, making it substantially less sensitive to outliers and non-normality than the classical Student or Welch t-test. The most widely used form is Yuen's test, which also accommodates unequal variances across groups.
ScholarGateJeu de données
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  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Robust Effect Size Analysis · Robust independent samples t-test. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare