中介效应估计中的混杂因素。
Confounding in the Estimation of Mediation Effects.
作者信息
Li Yan, Bienias Julia L, Bennett David A
机构信息
Division of Biostatistics and Bioinformatics, Departments of Family and Preventive Medicine and Neurosciences, Alzheimer's Disease Cooperative Study, University of California, San Diego.
出版信息
Comput Stat Data Anal. 2007 Mar 1;51(6):3173-3186. doi: 10.1016/j.csda.2006.10.016.
A mediation effect explains the relationship of a risk factor and an outcome through a mediator variable which is a step in their pathway. Under the assumption of no cycling in the causal relationship, we consider various situations in which a fourth variable may interfere the estimation of a mediation effect as a confounding factor. Our asymptotic results, which are supported by a Monte Carlo study, show that adjusting for confounding factors under certain conditions might lead to biased estimates. A general guideline is provided for when it is appropriate to adjust for confounding factors in estimating a mediation effect. We apply the guideline to the estimation of the mediation effect of Alzheimer's disease pathology in the relationship between the Apolipoprotein E ε4 allele and cognitive function among 125 deceased participants from the Religious Orders Study, a longitudinal, clinical-pathologic study of aging and Alzheimer's disease.
中介效应通过一个中介变量来解释风险因素与结果之间的关系，该中介变量是它们路径中的一个环节。在因果关系无循环的假设下，我们考虑了各种情况，即第四个变量可能作为混杂因素干扰中介效应的估计。我们的渐近结果得到了蒙特卡洛研究的支持，结果表明在某些条件下对混杂因素进行调整可能会导致有偏差的估计。本文提供了一个通用指南，用于判断在估计中介效应时何时适合对混杂因素进行调整。我们将该指南应用于宗教团体研究中125名已故参与者的载脂蛋白E ε4等位基因与认知功能关系中阿尔茨海默病病理学中介效应的估计，宗教团体研究是一项关于衰老和阿尔茨海默病的纵向临床病理研究。
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