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通过随机过程的首次通过时间对半竞争风险进行建模。

Modeling of semi-competing risks by means of first passage times of a stochastic process.

作者信息

Sildnes Beate, Lindqvist Bo Henry

机构信息

Department of Mathematical Sciences, Norwegian University of Science and Technology, 7491, Trondheim, Norway.

BearingPoint, Tjuvholmen allé 3, 0252, Oslo, Norway.

出版信息

Lifetime Data Anal. 2018 Jan;24(1):153-175. doi: 10.1007/s10985-017-9399-y. Epub 2017 Jul 22.

Abstract

In semi-competing risks one considers a terminal event, such as death of a person, and a non-terminal event, such as disease recurrence. We present a model where the time to the terminal event is the first passage time to a fixed level c in a stochastic process, while the time to the non-terminal event is represented by the first passage time of the same process to a stochastic threshold S, assumed to be independent of the stochastic process. In order to be explicit, we let the stochastic process be a gamma process, but other processes with independent increments may alternatively be used. For semi-competing risks this appears to be a new modeling approach, being an alternative to traditional approaches based on illness-death models and copula models. In this paper we consider a fully parametric approach. The likelihood function is derived and statistical inference in the model is illustrated on both simulated and real data.

摘要

在半竞争风险模型中,我们考虑一个终端事件,比如人的死亡,以及一个非终端事件,比如疾病复发。我们提出了一个模型,其中终端事件的发生时间是随机过程首次达到固定水平c的时间,而非终端事件的发生时间则由同一过程首次达到随机阈值S的时间表示,假设该阈值与随机过程相互独立。为了明确起见,我们令随机过程为伽马过程,但也可以使用其他具有独立增量的过程。对于半竞争风险而言,这似乎是一种新的建模方法,是基于疾病-死亡模型和copula模型的传统方法的替代方案。在本文中,我们考虑一种完全参数化方法。推导了似然函数,并通过模拟数据和实际数据说明了模型中的统计推断。

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