A Powerful and Robust Test Statistic for Randomization Inference in Group-Randomized Trials with Matched Pairs of Groups
Article first published online: 6 JUL 2011
© 2011, The International Biometric Society
Volume 68, Issue 1, pages 75–84, March 2012
How to Cite
Zhang, K., Traskin, M. and Small, D. S. (2012), A Powerful and Robust Test Statistic for Randomization Inference in Group-Randomized Trials with Matched Pairs of Groups. Biometrics, 68: 75–84. doi: 10.1111/j.1541-0420.2011.01622.x
- Issue published online: 23 MAR 2012
- Article first published online: 6 JUL 2011
- Received May 2010. Revised April 2011. Accepted April 2011.
- Causal effect;
- Group-randomized trials;
- Randomization inference;
- Rank-based statistics;
Summary For group-randomized trials, randomization inference based on rank statistics provides robust, exact inference against nonnormal distributions. However, in a matched-pair design, the currently available rank-based statistics lose significant power compared to normal linear mixed model (LMM) test statistics when the LMM is true. In this article, we investigate and develop an optimal test statistic over all statistics in the form of the weighted sum of signed Mann-Whitney-Wilcoxon statistics under certain assumptions. This test is almost as powerful as the LMM even when the LMM is true, but it is much more powerful for heavy tailed distributions. A simulation study is conducted to examine the power.