方法对比

	稳健功效分析	稳健单因素方差分析
领域	统计学	统计学
方法族	Hypothesis test	Hypothesis test
起源年份	1990s–2000s	1951 (Welch); 1990s–2000s (trimmed-mean variants)
提出者	Rand R. Wilcox and colleagues	B. L. Welch; R. R. Wilcox (trimmed-mean extension)
类型	Power and sample-size planning	Robust parametric group comparison
开创性文献	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.	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
别名	power analysis under non-normality, distribution-free power analysis, robust sample-size determination, contamination-robust power	trimmed-mean ANOVA, Welch one-way ANOVA, heteroscedastic one-way ANOVA, robust ANOVA
相关	4	2
摘要	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.	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.