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ロバストな検出力分析×ロバスト独立標本t検定×
分野統計学統計学
系統Hypothesis testHypothesis test
提唱年1990s–2000s1974–1990s
提唱者Rand R. Wilcox and colleaguesRand R. Wilcox; Karen K. Yuen (trimmed-mean form)
種類Power and sample-size planningRobust parametric mean comparison
原典Luh, W.-M., & Guo, J.-H. (2010). Approximate sample size formulas for the two-sample trimmed mean test with unequal variances. British Journal of Mathematical and Statistical Psychology, 63(1), 83–100. link ↗Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
別名power analysis under non-normality, distribution-free power analysis, robust sample-size determination, contamination-robust powerYuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test
関連42
概要Robust power analysis computes the statistical power or required sample size for hypothesis tests that use robust estimators — such as trimmed means or Winsorized variances — instead of ordinary means and standard deviations. It protects against inflated or deflated power estimates that arise when data contain outliers, heavy tails, or skewness that violate classical normality assumptions.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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ScholarGate手法を比較: Robust power analysis · Robust independent samples t-test. 2026-06-18に以下より取得 https://scholargate.app/ja/compare