Hypothesis testClassical statistics

Robust Power Analysis

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.

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Sources

  1. 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. DOI: 10.1348/000711008X393692
  2. Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838

Related methods

ScholarGateRobust power analysis (Robust Statistical Power Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/robust-power-analysis