演講通知-Prof. Takeshi Emura 2023/11/22(星期三) 16:10~17:00
演講者：Prof. Takeshi Emura
講題：Factorial survival analysis for treatment effects under dependent censoring
摘要：Factorial analyses offer a powerful nonparametric means to detect main or interaction effects among multiple treatments. For survival outcomes, e.g. from clinical trials, such techniques can be adopted for comparing reasonable quantifications of treatment effects. The key difficulty to solve in survival analysis concerns proper handling of censoring. So far, all existing factorial analyses for survival data were developed under the independent censoring assumption, which is too strong for many applications. As a solution, the central aim of this article is to develop new methods for factorial survival analyses under quite general dependent censoring regimes. This will be accomplished by combining existing nonparametric methods for factorial survival analyses with techniques developed for survival copula models. As a result, we will present an appeal that exhibits sound performance in our simulation study. The new methods are illustrated in a real data analysis.