Mediation analysis is a strategy for understanding the mechanisms by which treatments or interventions affect later outcomes. Mediation analysis is frequently applied in randomized trial settings, but typically assumes: a) that randomized assignment is the exposure of interest as opposed to actual take-up of the intervention, and b) no unobserved confounding of the mediator-outcome relationship. In contrast to the rich literature on instrumental variable (IV) methods to estimate a total effect of a non-randomized exposure, there has been almost no research into using IV as an identification strategy in the presence of both exposure-outcome and mediator-outcome unobserved confounding. In response, we define and identify novel estimands -- complier interventional direct and indirect effects (i.e., IV mediational effects) in two scenarios: 1) with a single IV for the exposure, and 2) with two IVs, one for the exposure and another for the mediator, that may be related. We propose nonparametric, robust, efficient estimators, and apply them to a housing voucher experiment.
翻译:调解分析经常在随机审判环境中应用,但通常假设:(a) 随机派任是感兴趣的暴露,而不是实际接受干预,和(b) 没有注意到调解人-结果关系的混乱。与关于评估非随机接触总影响的工具变量(四)方法的丰富文献相比,几乎没有研究在暴露结果和调解人-结果未观察到的混杂情况下将IV作为一种识别战略。作为回应,我们界定并确定了两种情景中的新估计值 -- -- 遵守干预直接和间接影响(即,四类调解影响):1) 与单一的暴露四,2) 与可能相关的两个四,一个是暴露,一个是暴露,另一个是调解人。我们提出不对称性、稳健、高效的估算,并将其应用于住房凭证实验。