Robust repeated measures ANOVA
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. · ISBN 978-0123869838
- Keselman, H. J., Wilcox, R. R., & Lix, L. M. (2003). A generally robust approach to hypothesis testing in independent and correlated groups designs. Psychophysiology, 40(4), 586–596. · DOI 10.1111/1469-8986.00060
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