Work

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test

Year: 2026

Type: article

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.

Source: Statistics in Medicine

DOI: 10.1002/sim.70657

Authors: Zhilan Lou, Jun Shao, Ting Ye, Tuo Wang, Yanyao Yi, Yu Du

Institutions: Zhejiang University of Finance and Economics, University of Wisconsin–Madison, University of Washington, Eli Lilly (United States)

Language: English

Topic: Statistical Methods in Clinical Trials

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Jilin Office of Philosophy and Social Science

Award: G2611292585