CMStatistics 2017: Start Registration
View Submission - CMStatistics
B1168
Title: Exact inference on the restricted mean survival time Authors:  Lu Tian - Stanford University (United States) [presenting]
Abstract: In a randomized clinical trial with the time to event as the primary endpoint, one often evaluates the treatment effect by comparing the survival distributions from two groups. This can be achieved by for example estimating the hazard ratio under the popular proportional hazards (PH) model. However, when the hazard rate is very low, e.g., in safety studies, there may be too few observed events to warrant the valid asymptotic inferences based on the PH model. The exact inference including hypothesis testing and constructing 95\% confidence interval for the treatment effect is desired. We have developed an exact inference procedure for estimating the treatment effect based on the difference in restricted mean survival time between two arms, which is more appealing than hazard ratio in many applications. The proposed procedure is valid regardless of the number of events. We have also performed a simulation study to examine the finite sample performance of the proposed method.