Mediation analysis is used to explore how an established exposure-outcome relationship is influenced by a third variable (mediator). Multiple mediation analysis refers to the mediation analysis with multiple mediators. We propose to use the elastic net regularized linear regression in multiple mediation analysis when the number of potential mediators is large. In exploring the exposure-mediator-outcome relationship, we regularize coefficients of mediators in predicting the outcome. The penalization on the coefficient is inversely proportional to the association between the exposure variable and each mediator. Therefore, in estimating the effect of a mediator, the exposure-mediator and the mediatoroutcome associations are jointly considered. An R package, mmabig, is compiled for the proposed method. We perform a series of sensitivity and specificity analysis to examine factors that can influence the power of identifying important mediators. Further, we illustrate how to consider potential nonlinear associations among variables in the mediation analysis. Simulation studies have shown that the proposed mediation analysis method consistently obtain larger power when compared with its main competitors. The method is used with a real data set to explore factors that contribute to the racial disparity in survival rates among breast-cancer patients.

中文翻译：

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正则化多重中介分析

中介分析用于探索已建立的暴露-结果关系如何受到第三个变量（中介）的影响。多元中介分析是指具有多个中介因素的中介分析。我们建议在潜在中介数量很大时在多元中介分析中使用弹性网络正则化线性回归。在探索暴露-中介-结果关系时，我们在预测结果时调整中介系数。对系数的惩罚与暴露变量和每个介体之间的关联成反比。因此，在估计中介作用时，要联合考虑暴露-中介和中介结果关联。一个 R 包，mmabig, 是为建议的方法编译的。我们进行了一系列敏感性和特异性分析，以检查可能影响识别重要介质的能力的因素。此外，我们说明了如何在中介分析中考虑变量之间的潜在非线性关联。模拟研究表明，与主要竞争对手相比，所提出的中介分析方法始终获得更大的权力。该方法与真实数据集一起使用，以探索导致乳腺癌患者生存率种族差异的因素。