Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Eisenberg says college athletes much less likely than other students to seek help with mental health conditions

Mitchell finds children who lose fathers suffer at cellular level

Seefeldt says hard work alone won't allow poor to reach middle-class status in America

More News

Highlights

Neal Krause wins GSA's Robert Kleemeier Award

U-M awarded $58 million to develop ideas for preventing and treating health problems

Bailey, Eisenberg , and Fomby promoted at PSC

Former PSC trainee Eric Chyn wins PAA's Dorothy S. Thomas Award for best paper

More Highlights

Ben Hansen photo

Optimal full matching and related designs via network flows

Publication Abstract

Hansen, Ben, and S.O. Klopfer . 2006. "Optimal full matching and related designs via network flows." Journal of Computational and Graphical Statistics, 15(3): 609-627.

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.

DOI:10.1198/106186006X137047 (Full Text)

Browse | Search : All Pubs | Next