Optimal full matching and related designs via network flows
Optimal full matching and related designs via network flows
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DOI：
10.1198/106186006x137047
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发表时间：
2006-09-01
影响因子：
2.4
通讯作者：
Klopfer, Stephanie Olsen
中科院分区：
文献类型：
--
作者：
Hansen, Ben B.;Klopfer, Stephanie Olsen
在观察性研究的匹配分析中，协变量X的混杂通过比较一个显著组（Z = 1）与对照组（Z = 0）的成员来解决，只有当他们属于相同的匹配集时。因此，更好的匹配是那些匹配集在Z上表现出分散性而在X上表现出均匀性的匹配。对于Z轴上的离散度，配对匹配是最好的，可以创建组间均衡的匹配集;但实际数据对X轴上匹配对的均匀性有限制，通常是严重的限制。另一个极端是完全匹配，匹配集在X上尽可能均匀，而在Z上往往分散得很差，从而牺牲了效率。该算法首先对匹配集在X方向上的均匀性和Z方向上的离散性提出要求，然后判断这些要求的可行性。在可行的情况下，它在具有规定的Z-分散的匹配中选择对于X-均匀性最佳的匹配。为了说明，我们描述了该算法的使用在一项研究中比较妇女的男性的工作条件，我们比较我们的方法，一个常用的替代方案，贪婪匹配，这是既不是最佳的，也不灵活，但算法简单得多。比较发现有意义的优势，在偏见和效率方面，为我们更多的研究方法。
In the matched analysis of an observational study, confounding on covariates X is addressed by comparing members of a distinguished group (Z = 1) to controls (Z = 0) only when they belong to the same matched set. The better matchings, therefore, are those whose matched sets exhibit both dispersion in Z and uniformity in X. For dispersion in Z, pair matching is best, creating matched sets that are equally balanced between the groups; but actual data place limits, often severe limits, on matched pairs' uniformity in X. At the other extreme is full matching, the matched sets of which are as uniform in X as can be, while often so poorly dispersed in Z as to sacrifice efficiency.This article presents an algorithm for exploring the intermediate territory. Given requirements on matched sets' uniformity in X and dispersion in Z, the algorithm first decides the requirements' feasibility. In feasible cases, it furnishes a match that is optimal for X-uniformity among matches with Z-dispersion as stipulated. To illustrate, we describe the algorithm's use in a study comparing womens' to mens' working conditions; and we compare our method to a commonly used alternative, greedy matching, which is neither optimal nor as flexible but is algorithmically much simpler. The comparison finds meaningful advantages, in terms of both bias and efficiency, for our more studied approach.