Yin Qing, Jeong Jong-Hyeon, Qin Xu, Peddada Shyamal D, Adibi Jennifer J
Department of Biostatistics, University of Pittsburgh.
Department of Health and Human Development, University of Pittsburgh.
ArXiv. 2023 Oct 13:arXiv:2310.09185v1.
Often linear regression is used to perform mediation analysis. However, in many instances, the underlying relationships may not be linear, as in the case of placentalfetal hormones and fetal development. Although, the exact functional form of the relationship may be unknown, one may hypothesize the general shape of the relationship. For these reasons, we develop a novel shape-restricted inference-based methodology for conducting mediation analysis. This work is motivated by an application in fetal endocrinology where researchers are interested in understanding the effects of pesticide application on birth weight, with human chorionic gonadotropin (hCG) as the mediator. We assume a practically plausible set of nonlinear effects of on the birth weight and a linear relationship between pesticide exposure and hCG, with both exposure-outcome and exposure-mediator models being linear in the confounding factors. Using the proposed methodology on a population-level prenatal screening program data, with hCG as the mediator, we discovered that, while the natural direct effects suggest a positive association between pesticide application and birth weight, the natural indirect effects were negative.
线性回归常常被用于进行中介分析。然而，在许多情况下，潜在关系可能并非线性，胎盘 - 胎儿激素与胎儿发育的情况就是如此。尽管关系的确切函数形式可能未知，但人们可以推测关系的大致形状。出于这些原因，我们开发了一种基于形状受限推断的新颖方法来进行中介分析。这项工作源于胎儿内分泌学中的一个应用，研究人员感兴趣的是了解农药施用对出生体重的影响，其中人绒毛膜促性腺激素（hCG）作为中介变量。我们假设农药对出生体重有一组实际合理的非线性效应，且农药暴露与hCG之间存在线性关系，暴露 - 结果模型和暴露 - 中介变量模型在混杂因素方面均为线性。在一个以人群为基础的产前筛查项目数据中，以hCG作为中介变量，使用所提出的方法，我们发现，虽然自然直接效应表明农药施用与出生体重之间存在正相关，但自然间接效应为负。
