Rubin Donald B
Department of Statistics, Harvard University, 1 Oxford Street, 7th Floor, Cambridge, MA 02138, USA.
Stat Med. 2007 Jan 15;26(1):20-36. doi: 10.1002/sim.2739.
For estimating causal effects of treatments, randomized experiments are generally considered the gold standard. Nevertheless, they are often infeasible to conduct for a variety of reasons, such as ethical concerns, excessive expense, or timeliness. Consequently, much of our knowledge of causal effects must come from non-randomized observational studies. This article will advocate the position that observational studies can and should be designed to approximate randomized experiments as closely as possible. In particular, observational studies should be designed using only background information to create subgroups of similar treated and control units, where 'similar' here refers to their distributions of background variables. Of great importance, this activity should be conducted without any access to any outcome data, thereby assuring the objectivity of the design. In many situations, this objective creation of subgroups of similar treated and control units, which are balanced with respect to covariates, can be accomplished using propensity score methods. The theoretical perspective underlying this position will be presented followed by a particular application in the context of the US tobacco litigation. This application uses propensity score methods to create subgroups of treated units (male current smokers) and control units (male never smokers) who are at least as similar with respect to their distributions of observed background characteristics as if they had been randomized. The collection of these subgroups then 'approximate' a randomized block experiment with respect to the observed covariates.
对于估计治疗的因果效应，随机实验通常被视为黄金标准。然而，由于各种原因，如伦理问题、费用过高或时间紧迫，进行随机实验往往不可行。因此，我们对因果效应的许多认识必须来自非随机观察性研究。本文将主张这样一种观点，即观察性研究能够且应该被设计成尽可能接近随机实验。具体而言，观察性研究应仅利用背景信息来创建类似的治疗组和对照组亚组，这里的“类似”是指它们背景变量的分布。非常重要的是，这项活动应在不获取任何结果数据的情况下进行，从而确保设计的客观性。在许多情况下，通过倾向得分方法可以实现对类似的治疗组和对照组亚组的客观创建，这些亚组在协变量方面是平衡的。本文将阐述这一观点的理论基础，随后介绍其在美国烟草诉讼背景下的一个具体应用。该应用使用倾向得分方法创建治疗组（当前男性吸烟者）和对照组（男性从不吸烟者）的亚组，这些亚组在观察到的背景特征分布方面至少与经过随机分组后的情况一样相似。然后，就观察到的协变量而言，这些亚组的集合“近似于”一个随机区组实验。
