Bandingkan metode

	Analisis Ukuran Efek Robust	Uji-t sampel independen yang robust
Bidang	Statistika	Statistika
Keluarga	Hypothesis test	Hypothesis test
Tahun asal	2005 (formalized)	1974–1990s
Pencetus	Algina, Keselman & Penfield; Wilcox	Rand R. Wilcox; Karen K. Yuen (trimmed-mean form)
Tipe	Robust effect size estimation	Robust parametric mean comparison
Sumber perintis	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
Alias	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
Terkait	5	2
Ringkasan	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.