Am J Epidemiol. 2021 Aug 1;190(8):1632-1642. doi: 10.1093/aje/kwaa270.
In this article, we examine study designs for extending (generalizing or transporting) causal inferences from a randomized trial to a target population. Specifically, we consider nested trial designs, where randomized individuals are nested within a sample from the target population, and nonnested trial designs, including composite data-set designs, where observations from a randomized trial are combined with those from a separately obtained sample of nonrandomized individuals from the target population. We show that the counterfactual quantities that can be identified in each study design depend on what is known about the probability of sampling nonrandomized individuals. For each study design, we examine identification of counterfactual outcome means via the g-formula and inverse probability weighting. Last, we explore the implications of the sampling properties underlying the designs for the identification and estimation of the probability of trial participation.
在本文中，我们研究了将随机试验的因果推论扩展（推广或转移）到目标人群的研究设计。具体来说，我们考虑了嵌套试验设计，其中随机个体嵌套在目标人群的样本中，以及非嵌套试验设计，包括组合数据集设计，其中随机试验的观测值与从目标人群中另外获得的非随机个体样本的观测值相结合。我们表明，在每种研究设计中可以确定的反事实数量取决于对抽样非随机个体的概率的了解程度。对于每种研究设计，我们通过 g 公式和逆概率加权来检验反事实结果平均值的识别。最后，我们探讨了设计背后的抽样性质对试验参与概率的识别和估计的影响。
