Transported mediation effects may contribute to understanding how interventions work differently when applied to new populations. However, we are not aware of any estimators for such effects. Thus, we propose two doubly robust, efficient estimators of transported stochastic (also called randomized interventional) direct and indirect effects. We demonstrate their finite sample properties in a simulation study. We then apply the preferred substitution estimator to longitudinal data from the Moving to Opportunity Study, a large-scale housing voucher experiment, to transport stochastic indirect effect estimates of voucher receipt in childhood on subsequent risk of mental health or substance use disorder mediated through parental employment across sites, thereby gaining understanding of drivers of the site differences. This article is protected by copyright. All rights reserved.

中文翻译：

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将随机的直接和间接影响传递给新人群

传递的中介效应可能有助于理解干预措施在应用于新人群时如何以不同的方式发挥作用。然而，我们不知道有任何对此类影响的估计。因此，我们提出了两个双重稳健、有效的传输随机（也称为随机干预）直接和间接效应的估计器。我们在模拟研究中展示了它们的有限样本特性。然后，我们将首选替代估计量应用于“转向机会研究”（一项大规模住房券实验）的纵向数据，以传输儿童时期收到的住房券对随后通过父母就业介导的心理健康或药物滥用障碍风险的随机间接影响估计跨站点，从而了解站点差异的驱动因素。本文受版权保护。版权所有。