Matching Without Groups

Chapter
Part of the Springer Series in Statistics book series (SSS)

Abstract

Optimal matching without groups, or optimal nonbipartite matching, offers many additional options for matched designs in both observational studies and experiments. One starts with a square, symmetric distance matrix with one row and one column for each subject recording the distance between any two subjects. Then the subjects are divided into pairs to minimize the total distance within pairs. The method may be used to match with doses of treatment, or with multiple control groups, or as an aid to risk-set matching. An extended discussion of Card and Krueger’s study of the minimum wage is used to illustrate.

Keywords

Alan Silber 

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Copyright information

© Springer-Verlag New York 2010

Authors and Affiliations

  1. 1.Statistics Department Wharton SchoolUniversity of PennsylvaniaPhiladelphiaUSA

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