B0389
Title: Surviving the multiple testing problem: RMST-based tests in general factorial designs
Authors: Merle Munko - Otto-von-Guericke University Magdeburg (Germany) [presenting]
Marc Ditzhaus - Otto-von-Guericke University Magdeburg (Germany)
Abstract: Several methods in survival analysis are based on the proportional hazards assumption. However, this assumption is very restrictive and often not justifiable in practice. Therefore, effect estimands that do not rely on the proportional hazards assumption, such as the restricted mean survival time (RMST), are highly desirable in practical applications. The RMST is defined as the area under the survival curve up to a prespecified time point and, thus, summarizes the survival curve into a meaningful estimand. For two-sample comparisons based on the RMST, there is an inflation of the type-I error of the asymptotic test for small samples and, therefore, a two-sample permutation test has already been developed. The first goal is to further extend the permutation test for general factorial designs and general contrast hypotheses by considering a Wald-type test statistic and its asymptotic behaviour. Additionally, a groupwise bootstrap approach is considered. In the second step, multiple tests for the RMST are developed to infer several null hypotheses simultaneously. Hereby, the asymptotically exact dependence structure between the local test statistics is incorporated to gain more power. Finally, the small sample performance of the proposed global and multiple testing procedures is analyzed in simulations.
