Attributing effects to interactions.
Attributing effects to interactions.
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DOI：
10.1097/ede.0000000000000096
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
Tchetgen Tchetgen EJ
中科院分区：
文献类型：
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作者：
VanderWeele TJ;Tchetgen Tchetgen EJ
一个框架，允许研究人员估计一个曝光的影响，这是由于与第二次曝光的相互作用的一部分。我们发现，当两个曝光是独立的，一个曝光的总效果可以分解为一个条件的影响，曝光和组件由于相互作用。分解适用于差异或比率尺度。我们讨论了如何使用标准回归模型估计的组件，以及如何使用这些组件来评估的比例的总影响的主要曝光归因于与第二次曝光的相互作用。在其中一个曝光影响另一个曝光的设置中，使得两者不再独立，讨论了替代分解。在遗传流行病学的一个例子说明了各种分解。如果不可能对感兴趣的主要暴露进行干预，本文中描述的方法可以帮助研究人员确定其他变量，如果进行干预，将消除主要暴露影响的最大比例。
A framework is presented that allows an investigator to estimate the portion of the effect of one exposure that is attributable to an interaction with a second exposure. We show that when the two exposures are independent, the total effect of one exposure can be decomposed into a conditional effect of that exposure and a component due to interaction. The decomposition applies on difference or ratio scales. We discuss how the components can be estimated using standard regression models, and how these components can be used to evaluate the proportion of the total effect of the primary exposure attributable to the interaction with the second exposure. In the setting in which one of the exposures affects the other, so that the two are no longer independent, alternative decompositions are discussed. The various decompositions are illustrated with an example in genetic epidemiology. If it is not possible to intervene on the primary exposure of interest, the methods described in this paper can help investigators to identify other variables that, if intervened upon, would eliminate the largest proportion of the effect of the primary exposure.