Сравнение методов

	Анализ робастных размеров эффекта	Робастная однофакторная дисперсионная структура ANOVA
Область	Статистика	Статистика
Семейство	Hypothesis test	Hypothesis test
Год появления	2005 (formalized)	1951 (Welch); 1990s–2000s (trimmed-mean variants)
Автор метода	Algina, Keselman & Penfield; Wilcox	B. L. Welch; R. R. Wilcox (trimmed-mean extension)
Тип	Robust effect size estimation	Robust parametric group comparison
Основополагающий источник	Algina, 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.	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
Другие названия	robust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean difference	trimmed-mean ANOVA, Welch one-way ANOVA, heteroscedastic one-way ANOVA, robust ANOVA
Связанные	5	2
Сводка	Robust 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.	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.