论文标题
概括和运输有关治疗分配影响的推论
Generalizing and transporting inferences about the effects of treatment assignment subject to non-adherence
论文作者
论文摘要
我们在对治疗分配的完美和不完美的遵守情况下，讨论因果估计值的可识别性。我们考虑一个设置试验数据包含有关基线协变量，基线分配，基线干预（点处理）和结果的信息；来自非随机个体的数据仅包含基线协变量的信息。在这种情况下，我们在完美的依从性下审查了识别结果，并研究了两个例子，其中不遵守严重限制了将治疗分配影响推理到目标人群的能力。在第一个示例中，试验参与对治疗收据有直接影响，并通过治疗收据对结果（通过依从性的“试验效应”）。在第二个示例中，参与试验具有未衡量的治疗收据的常见原因。在这两个示例中，分配对目标人群中结果的影响是无法识别的。但是，在第一个示例中，可以识别出影响依从性和分配治疗的扩大试验活动的联合干预措施的影响。我们得出的结论是，概括性和可运输性分析应考虑通过遵守和选择参与的效果，以影响影响依从性的未测量因素。
We discuss the identifiability of causal estimands for generalizability and transportability analyses, both under perfect and imperfect adherence to treatment assignment. We consider a setting where the trial data contain information on baseline covariates, assignment at baseline, intervention at baseline (point treatment), and outcomes; and where the data from non-randomized individuals only contain information on baseline covariates. In this setting, we review identification results under perfect adherence and study two examples in which non-adherence severely limits the ability to transport inferences about the effects of treatment assignment to the target population. In the first example, trial participation has a direct effect on treatment receipt and, through treatment receipt, on the outcome (a "trial engagement effect" via adherence). In the second example, participation in the trial has unmeasured common causes with treatment receipt. In both examples, the effect of assignment on the outcome in the target population is not identifiable. In the first example, however, the effect of joint interventions to scale-up trial activities that affect adherence and assign treatment is identifiable. We conclude that generalizability and transportability analyses should consider trial engagement effects via adherence and selection for participation on the basis of unmeasured factors that influence adherence.
