In this paper we revisit some common recommendations regarding the analysis of matched-pair and stratified experimental designs in the presence of attrition. Our main objective is to clarify a number of well-known claims about the practice of dropping pairs with an attrited unit when analyzing matched-pair designs. Contradictory advice appears in the literature about whether or not dropping pairs is beneficial or harmful, and stratifying into larger groups has been recommended as a resolution to the issue. To address these claims, we derive the estimands obtained from the difference-in-means estimator in a matched-pair design both when the observations from pairs with an attrited unit are retained and when they are dropped. We find limited evidence to support the claims that dropping pairs helps recover the average treatment effect, but we find that it may potentially help in recovering a convex weighted average of conditional average treatment effects. We report similar findings for stratified designs when studying the estimands obtained from a regression of outcomes on treatment with and without strata fixed effects.
翻译:在本文中,我们重新审视了有关在自然减员的情况下分析匹配和分层实验设计的一些共同建议。我们的主要目标是在分析匹配和分层实验设计时,澄清一些众所周知的关于用微小单元丢掉配对的做法的主张。文献中出现了关于投下配对是否有益或有害的意见,作为解决问题的解决方案,建议分为较大的群体。为了解决这些主张,我们在匹配和分层试验设计中从不同的估量器中获得的估量值中得出,在保留用微小单元的对配方的观察结果时,以及在它们被丢弃时,我们发现支持关于投下配方有助于恢复平均治疗效果的主张的证据有限,但我们认为,这可能有助于恢复对等分层加权平均有条件平均治疗效果。我们报告在研究从对治疗和无层次固定效果的回归结果中得出的估计值时,对分层设计也有类似的结论。