方法对比

	稳健重复测量方差分析	稳健Friedman检验
领域	统计学	统计学
方法族	Hypothesis test	Hypothesis test
起源年份	1990s–2000s	1990s–2000s
提出者	Rand R. Wilcox	Extension of Friedman (1937); robust variants developed by Wilcox and colleagues
类型	Robust parametric mean comparison	Robust nonparametric repeated measures comparison
开创性文献	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
别名	robust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVA	robust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust test
相关	6	6
摘要	Robust repeated measures ANOVA tests whether population trimmed means differ across three or more repeated conditions or time points measured on the same subjects. By replacing ordinary means with 20% trimmed means and replacing variances with Winsorized estimates, it maintains acceptable Type I error and power when data are non-normal, skewed, or contain outliers — conditions under which classical repeated measures ANOVA routinely breaks down.	The robust Friedman test is a nonparametric procedure for comparing three or more related (within-subjects) conditions that replaces standard ranking or mean-based summaries with robust location estimates — typically trimmed means or Winsorized statistics — to reduce the influence of outliers and heavy-tailed distributions on the inference.