Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Stat Med. 2019 Feb 20;38(4):512-529. doi: 10.1002/sim.7945. Epub 2018 Sep 6.
Mediation analysis provides an attractive causal inference framework to decompose the total effect of an exposure on an outcome into natural direct effects and natural indirect effects acting through a mediator. For binary outcomes, mediation analysis methods have been developed using logistic regression when the binary outcome is rare. These methods will not hold in practice when a disease is common. In this paper, we develop mediation analysis methods that relax the rare disease assumption when using logistic regression. We calculate the natural direct and indirect effects for common diseases by exploiting the relationship between logit and probit models. Specifically, we derive closed-form expressions for the natural direct and indirect effects on the odds ratio scale. Mediation models for both continuous and binary mediators are considered. We demonstrate through simulation that the proposed method performs well for common binary outcomes. We apply the proposed methods to analyze the Normative Aging Study to identify DNA methylation sites that are mediators of smoking behavior on the outcome of obstructed airway function.
中介分析提供了一个有吸引力的因果推理框架，可将暴露对结果的总效应分解为通过中介作用的自然直接效应和自然间接效应。对于二分类结局，当二分类结局罕见时，已经开发了使用逻辑回归的中介分析方法。当疾病很常见时，这些方法在实践中不成立。本文开发了在使用逻辑回归时放宽罕见疾病假设的中介分析方法。我们通过利用逻辑和概率单位模型之间的关系，计算常见疾病的自然直接和间接效应。具体来说，我们推导出了在优势比尺度上的自然直接和间接效应的封闭形式表达式。同时考虑了连续和二分类中介的中介模型。我们通过模拟证明了该方法对于常见的二分类结局表现良好。我们将提出的方法应用于分析规范老化研究，以确定 DNA 甲基化位点是否为吸烟行为对气道功能阻塞结果的中介。
