Causal mediation analysis seeks to determine whether an independent variable affects a response variable directly or whether it does so indirectly, by way of a mediator. The existing statistical tests to determine the existence of an indirect effect are overly conservative or have inflated type I error. In this article, we propose two methods based on the principle of intersection-union tests that offer improvements in power while controlling the type I error. We demonstrate the advantages of the proposed methods through extensive simulation. Finally, we provide an application to a large proteomic study.

翻译：独立变量直接影响反应变量,还是间接影响反应变量,则由调解人进行调解; 现有统计测试以确定是否存在间接影响,这种测试过于保守,或夸大了I型错误; 本条根据跨工会测试原则提出了两种方法,在控制I型错误的同时,可以改善权力; 我们通过广泛模拟,展示了拟议方法的优点; 最后, 我们为大规模蛋白质组研究提供了应用。