论文标题
选择偏见的潜在结果方法
A potential outcomes approach to selection bias
论文作者
论文摘要
我们提出了使用潜在结果在分析流行病学中选择偏差的新定义。该定义捕获了在结构方法下的选择偏见（在研究中进行选择的条件在定向的无环图中从暴露于疾病的疾病中打开了一条非原因路径）和传统的定义（其中给定的缔合量度在研究样本与有资格纳入的人群之间有所不同）。它是非参数，并且可以使用远离零假设的单个世界干预图分析这种方法下的选择偏差。它允许对混杂和选择偏见进行同时分析，它明确将研究参与者的选择与使用研究数据的因果效应估算，并且可以适应描述性流行病学中的选择偏见。通过示例，我们表明，这种方法为可以产生选择偏见的各种机制提供了一种新的观点，并简化了匹配的研究和病例研究研究中选择偏差的分析。
We propose a novel definition of selection bias in analytic epidemiology using potential outcomes. This definition captures selection bias under both the structural approach (where conditioning on selection into the study opens a noncausal path from exposure to disease in a directed acyclic graph) and the traditional definition (where a given measure of association differs between the study sample and the population eligible for inclusion). It is nonparametric, and selection bias under this approach can be analyzed using single-world intervention graphs both under and away from the null hypothesis. It allows the simultaneous analysis of confounding and selection bias, it explicitly links the selection of study participants to the estimation of causal effects using study data, and it can be adapted to handle selection bias in descriptive epidemiology. Through examples, we show that this approach provides a novel perspective on the variety of mechanisms that can generate selection bias and simplifies the analysis of selection bias in matched studies and case-cohort studies.
