Baker Stuart G, Lindeman Karen S, Kramer Barnett S
National Institutes of Health, USA.
Int J Biostat. 2011;7(1):25. doi: 10.2202/1557-4679.1338. Epub 2011 May 20.
The paired availability design for historical controls postulated four classes corresponding to the treatment (old or new) a participant would receive if arrival occurred during either of two time periods associated with different availabilities of treatment. These classes were later extended to other settings and called principal strata. Judea Pearl asks if principal stratification is a goal or a tool and lists four interpretations of principal stratification. In the case of the paired availability design, principal stratification is a tool that falls squarely into Pearl's interpretation of principal stratification as "an approximation to research questions concerning population averages." We describe the paired availability design and the important role played by principal stratification in estimating the effect of receipt of treatment in a population using data on changes in availability of treatment. We discuss the assumptions and their plausibility. We also introduce the extrapolated estimate to make the generalizability assumption more plausible. By showing why the assumptions are plausible we show why the paired availability design, which includes principal stratification as a key component, is useful for estimating the effect of receipt of treatment in a population. Thus, for our application, we answer Pearl's challenge to clearly demonstrate the value of principal stratification.
历史对照的配对可及性设计假定了四类情况，这四类情况对应于如果参与者在与治疗的不同可及性相关的两个时间段中的任何一个时间段到达时将接受的治疗（旧治疗或新治疗）。这些类别后来扩展到其他情况，并被称为主要分层。朱迪亚·珀尔提出主要分层是一个目标还是一种工具，并列出了主要分层的四种解释。在配对可及性设计的情况下，主要分层是一种工具，它完全符合珀尔对主要分层的解释，即“对有关总体平均值的研究问题的一种近似”。我们描述了配对可及性设计以及主要分层在利用治疗可及性变化的数据估计总体中接受治疗的效果时所起的重要作用。我们讨论了这些假设及其合理性。我们还引入了外推估计，以使可推广性假设更合理。通过说明这些假设为何合理，我们展示了为何包含主要分层作为关键组成部分的配对可及性设计对于估计总体中接受治疗的效果是有用的。因此，对于我们的应用，我们回应了珀尔的挑战，即清楚地证明主要分层的价值。
