Monday, Aug 5: 2:00 PM - 3:50 PM
2994
Contributed Posters
Oregon Convention Center
The log-rank test is widely used in 2-arm clinical trials to compare survival distributions between groups. Design of clinical trials utilizing the log-rank test requires power calculations under the alternative hypothesis. Various distributional approximations for the log-rank test statistic under the alternative hypothesis have been proposed for power determination. Bernstein and Lagakos (1978) use an exponential MLE test for power calculation. Schoenfeld's (1981) method depends on a normal approximation with variance derived under local alternatives. Luo et al. (2019) and Yung and Liu (2020) derive a different asymptotic variance which also requires local alternatives. In practice, a local alternative assumption may unreasonable for large effects and modest sample sizes. Practical guidance is needed to guide selection of a power calculation method. We conduct a comprehensive simulation study comparing power calculation methods for the log-rank test and compare the underlying distributional assumptions of the mean and variance. This work provides guidance for practitioners and highlights the need for deriving the distribution of the log-rank test under general alternatives.
log-rank test
asymptotic theory
clinical trial design
survival analysis
Main Sponsor
Biometrics Section