A signed-rank test for clustered data

Biometrics. 2008 Jun;64(2):501-7. doi: 10.1111/j.1541-0420.2007.00923.x. Epub 2007 Oct 26.


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.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Biometry / methods*
  • Cluster Analysis*
  • Computer Simulation
  • Data Interpretation, Statistical*
  • Matched-Pair Analysis*
  • Models, Statistical*