Jiang Zhichao, VanderWeele Tyler J
Am J Epidemiol. 2015 Jul 15;182(2):105-8. doi: 10.1093/aje/kwv059. Epub 2015 May 5.
Assessment of indirect effects is useful for epidemiologists interested in understanding the mechanisms of exposure-outcome relationships. A traditional way of estimating indirect effects is to use the "difference method," which is based on regression analysis in which one adds a possible mediator to the regression model and examines whether the coefficient for the exposure changes. The difference method has been criticized for lacking a causal interpretation when it is used with logistic regression. In this article, we use the counterfactual framework to define the natural indirect effect (NIE) and assess the relationship between the NIE and the difference method. We show that under appropriate assumptions, the difference method consistently estimates the NIE for continuous outcomes and is always conservative for binary outcomes. Thus, the difference method can be used to provide evidence for the presence of mediation but not for the absence of mediation.
对于有兴趣了解暴露-结局关系机制的流行病学家来说，评估间接效应是有用的。估计间接效应的传统方法是使用“差异法”，该方法基于回归分析，即在回归模型中加入一个可能的中介变量，然后检查暴露变量的系数是否发生变化。当差异法与逻辑回归一起使用时，因其缺乏因果解释而受到批评。在本文中，我们使用反事实框架来定义自然间接效应（NIE），并评估NIE与差异法之间的关系。我们表明，在适当的假设下，差异法能一致地估计连续结局的NIE，而对于二元结局总是保守的。因此，差异法可用于为中介作用的存在提供证据，但不能用于证明中介作用不存在。
