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Sample size computation for two-sample noninferiority log-rank test
Sin-Ho Jung1, Sun J Kang, Linda M McCall
1Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA. jung0005@mc.duke.edu
Abstract:
When an experimental therapy is less extensive, less toxic, or less expensive than a standard therapy, we may want to prove that the former is not worse than the latter through a noninferiority trial. In this article, we discuss a modification of the log-rank test for noninferiority trials with survival endpoint and propose a sample size formula that can be used in designing such trials. Performance of our sample size formula is investigated through simulations. Our formula is applied to design a real clinical trial.
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