How Wrong Can a Rank-Based Sample-Size Calculation Be? A Sharp Bound of 16/9 for Ordinal Outcomes
Rank-based tests need no distributional assumptions to be valid, but the sample size they require does depend on the shapes of the two outcome distributions, which are unknown at the design stage. Standard practice substitutes a variance calibrated under the null. We ask how wrong that substitution can be. Writing $\Pi...