A Fast Algorithm for Maximal Propensity Score Matching

Результат исследования: Научные публикации в периодических изданияхстатьярецензирование

3 Цитирования (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.

Язык оригиналаанглийский
Страницы (с-по)477-495
Число страниц19
ЖурналMethodology and Computing in Applied Probability
Номер выпуска2
СостояниеОпубликовано - 1 июн. 2020


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