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Covariate Adjustment for Wilcoxon Two Sample Statistic and Test
Zhilan Lou1, Jun Shao2, Ting Ye3
1School of Data Sciences, Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.
Abstract:
We apply covariate adjustment to the Wilcoxon two sample statistic and Wilcoxon-Mann-Whitney test in comparing two treatments. The covariate adjustment through calibration not only improves efficiency in estimation/inference but also widens the application scope of the Wilcoxon two sample statistic and Wilcoxon-Mann-Whitney test to situations where covariate-adaptive randomization is used. We motivate how to adjust covariates to reduce variance, establish the asymptotic distribution of adjusted Wilcoxon two sample statistic, and provide explicitly the guaranteed efficiency gain. The asymptotic distribution of adjusted Wilcoxon two sample statistic is invariant to all commonly used covariate-adaptive randomization schemes so that a unified formula can be used in inference regardless of which covariate-adaptive randomization is applied.
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