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Yongzhao Shao

New York University School of Medicine



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Zhaoyin Zhu

NYU



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167 – Special Issues in Modeling

On Effect Sizes for Nonparametric Comparison of Censored Survival Outcomes

Sponsor: Korean International Statistical Society
Keywords: censored survival outcome, effect size, non-parametric test, time-to-event endpoint, sample size, clinical trials

Yongzhao Shao

New York University School of Medicine

Zhaoyin Zhu

NYU

Survival outcomes are frequently randomly censored with unknown censoring distributions. Due to complexities caused by censoring, useful effect sizes for nonparametric comparison of censored survival outcomes have not been systematically investigated despite existence of several well known nonparametric tests such as the log-rank test and Wilcoxon test. Effect size generally emphasizes the magnitude of the difference between the studied endpoints rather than confounding this with sample size as in the case of p-value. This paper investigates weakness and advantages of existing and newly proposed effect sizes for the nonparametric comparison of time-to-event outcomes.

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