Title: Model Identifiability for Bivariate Failure Time Data with Competing Risks: Parametric Cause-specific Hazards and Non-parametric Frailty Show Chinese title

Title: 双变量失效时间数据中基于竞争风险的模型可识别性：特定原因的风险率参数化和非参数 frailty

Abstract: One of the commonly used approaches to capture dependence in multivariate survival data is through the frailty variables. The identifiability issues should be carefully investigated while modeling multivariate survival with or without competing risks. The use of non-parametric frailty distribution(s) is sometimes preferred for its robustness and flexibility properties. In this paper, we consider modeling of bivariate survival data with competing risks through four different kinds of non-parametric frailty and parametric baseline cause-specific hazard functions to investigate the corresponding model identifiability. We make the common assumption of the frailty mean being equal to unity. Show Chinese abstract

Abstract: 在多变量生存数据中捕捉依赖关系的常用方法之一是通过易感变量。在建模多变量生存数据（有或没有竞争风险）时，应仔细调查辨识性问题。有时，由于非参数易感分布的稳健性和灵活性特性，人们更喜欢使用非参数易感分布。本文中，我们考虑通过四种不同类型的非参数易感性和参数基线原因特定风险函数来建模具有竞争风险的双变量生存数据，以研究相应的模型辨识性。我们做出了常见的假设，即易感变量的均值等于1。