A Fast Algorithm for Maximal Propensity Score Matching

Pavel S. Ruzankin ()
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Pavel S. Ruzankin: Sobolev Institute of Mathematics

Methodology and Computing in Applied Probability, 2020, vol. 22, issue 2, 477-495

Abstract: Abstract We present a new algorithm which detects the maximal possible number of matched disjoint pairs satisfying a given caliper when a bipartite matching is done with respect to a scalar index (e.g., propensity score), and constructs a corresponding matching. Variable width calipers are compatible with the technique, provided that the width of the caliper is a Lipschitz function of the index. If the observations are ordered with respect to the index then the matching needs O(N) operations, where N is the total number of subjects to be matched. The case of 1-to-n matching is also considered. We offer also a new fast algorithm for optimal complete one-to-one matching on a scalar index when the treatment and control groups are of the same size. This allows us to improve greedy nearest neighbor matching on a scalar index.

Keywords: Propensity score matching; Nearest neighbor matching; Matching with caliper; Variable width caliper; 92C50; 62P10; 05C70 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11009-019-09718-4

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