  Clinical trials often involve the assessment of multiple endpoints to
comprehensively evaluate the efficacy and safety of interventions. In the work,
we consider a global nonparametric testing procedure based on multivariate rank
for the analysis of multiple endpoints in clinical trials. Unlike other
existing approaches that rely on pairwise comparisons for each individual
endpoint, the proposed method directly incorporates the multivariate ranks of
the observations. By considering the joint ranking of all endpoints, the
proposed approach provides robustness against diverse data distributions and
censoring mechanisms commonly encountered in clinical trials. Through extensive
simulations, we demonstrate the superior performance of the multivariate
rank-based approach in controlling type I error and achieving higher power
compared to existing rank-based methods. The simulations illustrate the
advantages of leveraging multivariate ranks and highlight the robustness of the
approach in various settings. The proposed method offers an effective tool for
the analysis of multiple endpoints in clinical trials, enhancing the
reliability and efficiency of outcome evaluations.
