Li Fan, Hong Hwanhee, Stuart Elizabeth A
Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.
Center for Methods in Implementation and Prevention Science, Yale University School of Public Health, New Haven, Connecticut, USA.
Commun Stat Theory Methods. 2023;52(16):5767-5798. doi: 10.1080/03610926.2021.2020291. Epub 2021 Dec 29.
When effect modifiers influence the decision to participate in randomized trials, generalizing causal effect estimates to an external target population requires the knowledge of two scores - the propensity score for receiving treatment and the sampling score for trial participation. While the former score is known due to randomization, the latter score is usually unknown and estimated from data. Under unconfounded trial participation, we characterize the asymptotic efficiency bounds for estimating two causal estimands - the population average treatment effect and the average treatment effect among the non-participants - and examine the role of the scores. We also study semiparametric efficient estimators that directly balance the weighted trial sample toward the target population, and illustrate their operating characteristics via simulations.
当效应修饰因素影响参与随机试验的决策时，将因果效应估计推广到外部目标人群需要了解两个得分——接受治疗的倾向得分和试验参与的抽样得分。虽然由于随机化，前一个得分是已知的，但后一个得分通常是未知的，需要从数据中估计。在无混杂试验参与的情况下，我们刻画了估计两个因果估计量——总体平均治疗效应和非参与者中的平均治疗效应——的渐近效率界，并研究了得分的作用。我们还研究了直接将加权试验样本向目标人群平衡的半参数有效估计量，并通过模拟说明了它们的操作特征。
