English

A fast algorithm for maximal propensity score matching

Computation 2022-07-20 v8 Data Structures and Algorithms

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)O(N) operations, where NN is the total number of subjects to be matched. The case of 1-to-nn 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.

Keywords

Cite

@article{arxiv.1701.02201,
  title  = {A fast algorithm for maximal propensity score matching},
  author = {Pavel S. Ruzankin},
  journal= {arXiv preprint arXiv:1701.02201},
  year   = {2022}
}
R2 v1 2026-06-22T17:44:49.563Z