VanderWeele Tyler J, Shpitser Ilya
Departments of Epidemiology and Biostatistics, Harvard School of Public Health 677 Huntington Avenue, Boston, Massachusetts 02115
Department of Epidemiology, Harvard School of Public Health 677 Huntington Avenue, Boston, Massachusetts 02115
Ann Stat. 2013 Feb;41(1):196-220. doi: 10.1214/12-aos1058.
The causal inference literature has provided a clear formal definition of confounding expressed in terms of counterfactual independence. The causal inference literature has not, however, produced a clear formal definition of a confounder, as it has given priority to the concept of confounding over that of a confounder. We consider a number of candidate definitions arising from various more informal statements made in the literature. We consider the properties satisfied by each candidate definition, principally focusing on (i) whether under the candidate definition control for all "confounders" suffices to control for "confounding" and (ii) whether each confounder in some context helps eliminate or reduce confounding bias. Several of the candidate definitions do not have these two properties. Only one candidate definition of those considered satisfies both properties. We propose that a "confounder" be defined as a pre-exposure covariate for which there exists a set of other covariates such that effect of the exposure on the outcome is unconfounded conditional on () but such that for no proper subset of () is the effect of the exposure on the outcome unconfounded given the subset. A variable that helps reduce bias but not eliminate bias we propose referring to as a "surrogate confounder."
因果推断文献已经给出了一个清晰的、用反事实独立性表述的混杂的形式化定义。然而,因果推断文献尚未给出一个清晰的、关于混杂因素的形式化定义,因为它将混杂的概念置于混杂因素的概念之上。我们考虑了文献中一些较为非正式的陈述所产生的多个候选定义。我们考察了每个候选定义所满足的性质,主要关注:(i)在候选定义下,对所有“混杂因素”进行控制是否足以控制“混杂”;(ii)在某些情况下,每个混杂因素是否有助于消除或减少混杂偏倚。有几个候选定义不具备这两个性质。在所考虑的候选定义中,只有一个满足这两个性质。我们建议将“混杂因素”定义为一个暴露前协变量,对于该协变量,存在一组其他协变量,使得在给定()的条件下,暴露对结局的效应是无混杂的,但对于()的任何真子集,在给定该子集的情况下,暴露对结局的效应并非无混杂。我们建议将一个有助于减少但不能消除偏倚的变量称为“替代混杂因素”。