A Signed‐Rank Test for Clustered Data

Abstract

Summary We consider the problem of comparing two outcome measures when the pairs are clustered. Using the general principle of within‐cluster resampling, we obtain a novel signed‐rank test for clustered paired data. We show by a simple informative cluster size simulation model that only our test maintains the correct size under a null hypothesis of marginal symmetry compared to four other existing signed rank tests; further, our test has adequate power when cluster size is noninformative. In general, cluster size is informative if the distribution of pair‐wise differences within a cluster depends on the cluster size. An application of our method to testing radiation toxicity trend is presented.