Abstract：
Selection bias has long been central in methodological discussions across epidemiology and other fields. In epidemiology, the concept of selection bias has been continually evolving over time. In this issue of the Journal, Mathur and Shpitser (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX) present simple graphical rules for using a Single World Intervention Graph (SWIG) to assess the presence of selection bias when estimating treatment effects in both the general population and a selected sample. Notably, the authors examine the setting in which the treatment affects selection, an issue not well-addressed in the existing literature on selection bias. To place the work by Mathur and Shpitser in context, we review the evolution of the concept of selection bias in epidemiology, with a primary focus on the developments in the last 20-30 years since the introduction of causal directed acyclic graphs (DAGs) to epidemiologic research.
摘要：
长期以来，选择偏见一直是流行病学和其他领域方法论讨论的中心。在流行病学中,随着时间的推移，选择偏差的概念一直在不断演变。在本期杂志中,Mathur和Shpitser(AmJEpidemium。XXXX;XXX（XX）：XXXX-XXXX）提出了使用单一世界干预图（SWIG）评估一般人群和选定样本中治疗效果时选择偏倚的存在的简单图形规则。值得注意的是,作者检查了治疗影响选择的设置，在现有的关于选择偏见的文献中，这是一个没有得到很好解决的问题。要将Mathur和Shpitser的作品放在上下文中，我们回顾了流行病学中选择偏差概念的演变，主要关注自将因果有向无环图（DAG）引入流行病学研究以来的过去20-30年的发展。
