A Fast Algorithm for Maximal Propensity Score Matching

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3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)477-495
Number of pages19
JournalMethodology and Computing in Applied Probability
Issue number2
Publication statusPublished - 1 Jun 2020


  • Matching with caliper
  • Nearest neighbor matching
  • Propensity score matching
  • Variable width caliper


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