Kim Yang-Jin
Department of Statistics, Sookmyung Women's University, Seoul, South Korea.
J Appl Stat. 2020 Mar 24;48(4):738-749. doi: 10.1080/02664763.2020.1744539. eCollection 2021.
Bivariate recurrent event data are observed when subjects are at risk of experiencing two different type of recurrent events. In this paper, our interest is to suggest statistical model when there is a substantial portion of subjects not experiencing recurrent events but having a terminal event. In a context of recurrent event data, zero events can be related with either the risk free group or a terminal event. For simultaneously reflecting both a zero inflation and a terminal event in a context of bivariate recurrent event data, a joint model is implemented with bivariate frailty effects. Simulation studies are performed to evaluate the suggested models. Infection data from AML (acute myeloid leukemia) patients are analyzed as an application.
当受试者面临经历两种不同类型的复发事件的风险时,就会观察到双变量复发事件数据。在本文中,我们感兴趣的是提出一种统计模型,该模型适用于存在相当一部分受试者未经历复发事件但发生了终末事件的情况。在复发事件数据的背景下,零事件可能与无风险组或终末事件相关。为了在双变量复发事件数据的背景下同时反映零膨胀和终末事件,我们实施了一个具有双变量脆弱效应的联合模型。进行了模拟研究以评估所提出的模型。作为应用,对急性髓系白血病(AML)患者的感染数据进行了分析。