Vertaile menetelmiä

	Robust Effect Size Analysis	Robustinen riippumattomien otosten t-testi
Tieteenala	Tilastotiede	Tilastotiede
Menetelmäperhe	Hypothesis test	Hypothesis test
Syntyvuosi	2005 (formalized)	1974–1990s
Kehittäjä	Algina, Keselman & Penfield; Wilcox	Rand R. Wilcox; Karen K. Yuen (trimmed-mean form)
Tyyppi	Robust effect size estimation	Robust parametric mean 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	Yuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test
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.	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.