Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking.
Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking.
复制标题
具有部分观察到的时变协变量的重复事件数据的混合效应模型：吸烟的生态瞬时评估。
DOI：
10.1111/biom.12416
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发表时间：
2016
期刊：
影响因子：
1.9
通讯作者：
Shiffman,Saul
中科院分区：
文献类型：
--
作者：
Rathbun,StephenL;Shiffman,Saul
吸烟是反复发作的典型例子。反复吸烟事件的模式可能取决于时变的协变量，包括情绪和环境变量。复发事件数据的固定效应和脆弱性模型假设吸烟者与时变协变量有共同的关联。我们开发了一个复发事件模型的混合效应版本，可用于描述吸烟者对这些协变量的反应的变化，可能导致基于个人的戒烟治疗的发展。我们的方法将Steele（1996）用于广义混合模型的改进EM算法扩展到具有部分观测时变协变量的循环事件数据。Rizopoulos， Verbeke和Lesaffre（2009）将Steele（1996）的算法扩展为循环事件数据和时变协变量的联合模型，该方法是Rizopoulos， Verbeke和Lesaffre（2009）方法的替代方法。我们的方法不需要时变协变量的模型，而是假设时变协变量根据已知强度的泊松点过程进行采样。我们的方法非常适合使用生态瞬间评估（EMA）收集数据，这是一种在行为科学中广泛使用的数据收集方法，用于收集研究对象使用个人数字助理（PDA）或智能手机等电子设备在日常环境中的情绪状态和反复事件的数据。
Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke, and Lesaffre (2009) who extended Steele's (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones.