Comparer des méthodes

	Analyse de puissance robuste	ANOVA robuste à un facteur
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1990s–2000s	1951 (Welch); 1990s–2000s (trimmed-mean variants)
Auteur d'origine	Rand R. Wilcox and colleagues	B. L. Welch; R. R. Wilcox (trimmed-mean extension)
Type	Power and sample-size planning	Robust parametric group comparison
Source fondatrice	Luh, W.-M., & Guo, J.-H. (2010). Approximate sample size formulas for the two-sample trimmed mean test with unequal variances. British Journal of Mathematical and Statistical Psychology, 63(1), 83–100.	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
Alias	power analysis under non-normality, distribution-free power analysis, robust sample-size determination, contamination-robust power	trimmed-mean ANOVA, Welch one-way ANOVA, heteroscedastic one-way ANOVA, robust ANOVA
Apparentées	4	2
Résumé	Robust power analysis computes the statistical power or required sample size for hypothesis tests that use robust estimators — such as trimmed means or Winsorized variances — instead of ordinary means and standard deviations. It protects against inflated or deflated power estimates that arise when data contain outliers, heavy tails, or skewness that violate classical normality assumptions.	Robust one-way ANOVA compares the central tendency of three or more independent groups while resisting the distorting effects of outliers and heterogeneous variances. By replacing ordinary means with trimmed means and ordinary variances with Winsorized variances, it maintains accurate Type I error control and strong power when classical ANOVA assumptions are violated.