Vertaile menetelmiä

	Robust Effect Size Analysis	Robust one-way ANOVA
Tieteenala	Tilastotiede	Tilastotiede
Menetelmäperhe	Hypothesis test	Hypothesis test
Syntyvuosi	2005 (formalized)	1951 (Welch); 1990s–2000s (trimmed-mean variants)
Kehittäjä	Algina, Keselman & Penfield; Wilcox	B. L. Welch; R. R. Wilcox (trimmed-mean extension)
Tyyppi	Robust effect size estimation	Robust parametric group comparison
Alkuperäislähde	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
Rinnakkaisnimet	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
Liittyvät	5	2
Tiivistelmä	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.