THE CONTROL OF CONFOUNDING BY INTERMEDIATE VARIABLES
THE CONTROL OF CONFOUNDING BY INTERMEDIATE VARIABLES
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DOI：
10.1002/sim.4780080608
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发表时间：
1989-06-01
影响因子：
2
通讯作者：
ROBINS, J
中科院分区：
文献类型：
--
作者：
ROBINS, J
在暴露对疾病影响的流行病学研究中，暴露与疾病的粗略关联可能由于一个或多个协变量的混杂而不能反映因果关联。既往大多数关于神经病学文献中混杂因素的讨论仅考虑了点暴露研究，即仅在随访开始时测量一次暴露和协变量状态的研究。在本文中，我们提供了适用于纵向研究的混杂定义，这些纵向研究在几个时间点获得了暴露、协变量和生命状态的数据。纵向研究和点暴露研究之间的一个重要区别是，在纵向研究中，时间依赖性协变量可以同时是从暴露到疾病的因果通路上的混杂因素和中间变量。在本文中，我提出了一个估计，扩展的标准化风险差，提供控制混杂的协变量，同时是一个混杂因素和中间变量。
In epidemiologic studies of the effect on an exposure on disease, the crude association of exposure with disease may fail to reflect a causal asociation due to confounding by one or more covariates. Most previous discussions of confounding in the epidemologic literature have considered only point exposure studies, that is, studies that measure exposure and covariate status only once, at start of follow-up. In this paper we offer definitions of confounding suitable for longitudinal studies that obtain data on exposure, covariate, and vital status at several points in time. An important difference between longitudinal studies and point exposure studies is that, in longitudinal studies, a time-dependent covariate can be simultaneously a confounder and an intermediate variable on the causal pathway from exposure to disease. In this paper I propose an estimator, the extended standardized risk difference, that provides control for confounding by a covariate that is simultaneously a confounder and an intemediate variable.