This paper provides robust estimators and efficient inference of causal effects involving multiple interacting mediators. Most existing works either impose a linear model assumption among the mediators or are restricted to handle conditionally independent mediators given the exposure. To overcome these limitations, we define causal and individual mediation effects in a general setting, and employ a semiparametric framework to develop quadruply robust estimators for these causal effects. We further establish the asymptotic normality of the proposed estimators and prove their local semiparametric efficiencies. The proposed method is empirically validated via simulated and real datasets concerning psychiatric disorders in trauma survivors.

翻译：本文针对涉及多个交互中介变量的因果效应，提供了稳健估计量及有效推断方法。现有研究大多对中介变量施加线性模型假设，或仅能处理给定暴露条件下条件独立的中介变量。为克服这些局限，本文在一般设定下定义了因果效应与个体中介效应，并采用半参数框架为这些因果效应构建了四倍稳健估计量。我们进一步证明了所提出估计量的渐近正态性及其局部半参数有效性。通过模拟数据集及涉及创伤幸存者精神障碍的真实数据集，本文对所提方法进行了实证验证。