Graduate School of Education, University of California, Riverside, Riverside, CA, USA.
Department of Statistics, University of California, Riverside, Riverside, CA, USA.
Stat Med. 2018 May 20;37(11):1810-1829. doi: 10.1002/sim.7632. Epub 2018 Mar 15.
Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals.
随机实验往往很复杂，因为存在治疗不依从的情况。这种挑战使得研究人员无法确定意向治疗（ITT）效应的中介部分，即归因于中介的指定治疗的效果。当只有一个中介时，有一种解决方案建议根据依从者的平均因果中介效应来确定中介 ITT 效应。然而，考虑到中介机制的复杂性质，自然可以假设存在多个通过因果路径进行中介的变量。受一项在随机干预研究中收集的数据集的实证分析的启发，我们开发了一种方法，用于估计当存在多个依赖于中介的变量和治疗不依从时，ITT 效应的中介部分。这使研究人员能够在存在治疗不依从的情况下，通过确定相关的中介变量，就如何增强干预效果做出明智的决策。我们提出了一种非参数估计程序，并对关键假设进行了敏感性分析。我们进行了蒙特卡罗模拟研究，以评估所提出方法的有限样本性能。通过对 JOBS II 数据的实证分析说明了该方法，其中使用了一项职业培训干预措施来防止失业人员的心理健康恶化。
