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September 2018 Optimal multilevel matching using network flows: An application to a summer reading intervention
Samuel D. Pimentel, Lindsay C. Page, Matthew Lenard, Luke Keele
Ann. Appl. Stat. 12(3): 1479-1505 (September 2018). DOI: 10.1214/17-AOAS1118


Many observational studies of causal effects occur in settings with clustered treatment assignment. In studies of this type, treatment is applied to entire clusters of units. For example, an educational intervention might be administered to all the students in a school. We develop a matching algorithm for multilevel data based on a network flow algorithm. Earlier work on multilevel matching relied on integer programming, which allows for balance targeting on specific covariates but can be slow with larger data sets. Although we cannot directly specify minimal levels of balance for individual covariates, our algorithm is fast and scales easily to larger data sets. We apply this algorithm to assess a school-based intervention through which students in treated schools were exposed to a new reading program during summer school. In one variant of the algorithm, where we match both schools and students, we change the causal estimand through optimal subset matching to better maintain common support. In a second variant, we relax the common support assumption to preserve the causal estimand by only matching on schools. We find that the summer intervention does not appear to increase reading test scores. In a sensitivity analysis, however, we determine that an unobserved confounder could easily mask a larger treatment effect.


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Samuel D. Pimentel. Lindsay C. Page. Matthew Lenard. Luke Keele. "Optimal multilevel matching using network flows: An application to a summer reading intervention." Ann. Appl. Stat. 12 (3) 1479 - 1505, September 2018.


Received: 1 November 2016; Revised: 1 October 2017; Published: September 2018
First available in Project Euclid: 11 September 2018

zbMATH: 06979639
MathSciNet: MR3852685
Digital Object Identifier: 10.1214/17-AOAS1118

Keywords: Causal inference , hierarchical/multilevel data , observational study , optimal matching

Rights: Copyright © 2018 Institute of Mathematical Statistics


Vol.12 • No. 3 • September 2018
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