Joint modelling of repeated measurements and time-to-event outcomes: The fourth Armitage lecture
Joint modelling of repeated measurements and time-to-event outcomes: The fourth Armitage lecture
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DOI：
10.1002/sim.3131
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发表时间：
2008-07-20
影响因子：
2
通讯作者：
Chetwynd, Amanda G.
中科院分区：
文献类型：
--
作者：
Diggle, Peter J.;Sousa, Ines;Chetwynd, Amanda G.
在许多纵向研究中，记录每个受试者的结果既包括在预先指定的时间进行的一系列重复测量，也包括特别感兴趣的事件发生的时间：例如死亡、症状复发或退出研究。每个受试者的事件时间可以被精确记录、间隔删失或右删失。术语“联合建模”是指对结果数据进行统计分析，同时考虑重复测量和事件发生时间结果之间的任何关联。在本文中，我们首先讨论联合建模的不同方法，并认为分析策略应取决于研究的科学重点。然后，我们详细描述一种特别简单、完全参数化的方法。最后，我们使用这种方法重新分析精神分裂症患者药物治疗临床试验的数据，其中事件时间是由于不良副作用退出研究的区间删失或右删失时间。版权所有 (C) 2007 John Wiley & Sons, Ltd.
In many longitudinal studies, the outcomes recorded on each subject include both a sequence of repeated measurements at pre-specified times and the time at which an event of particular interest occurs: for example, death, recurrence of symptoms or drop out from the Study. The event time for each subject may be recorded exactly, interval censored or right censored. The term joint modelling refers to the statistical analysis of the resulting data while taking account of any association between the repeated measurement and time-to-event outcomes. In this paper, we first discuss different approaches to joint modelling and argue that the analysis strategy should depend on the scientific focus of the study. We then describe in detail a particularly simple, fully parametric approach. Finally, we use this approach to re-analyse data from a clinical trial of drug therapies for schizophrenic patients, in which the event time is an interval-censored or right-censored time to withdrawal from the study due to adverse side effects. Copyright (C) 2007 John Wiley & Sons, Ltd.