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Аналіз робастних розмірів ефекту×Стійкий t-критерій для незалежних вибірок×
ГалузьСтатистикаСтатистика
РодинаHypothesis testHypothesis test
Рік появи2005 (formalized)1974–1990s
Автор методуAlgina, Keselman & Penfield; WilcoxRand R. Wilcox; Karen K. Yuen (trimmed-mean form)
ТипRobust effect size estimationRobust parametric mean comparison
Основоположне джерелоAlgina, 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. DOI ↗Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
Інші назвиrobust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean differenceYuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test
Пов'язані52
ПідсумокRobust 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.
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ScholarGateПорівняння методів: Robust Effect Size Analysis · Robust independent samples t-test. Отримано 2026-06-18 з https://scholargate.app/uk/compare