Algorithms and Complexities of Matching Variants in Covariate Balancing

Dorit S. Hochbaum; Asaf Levin; Xu Rao

doi:10.1287/opre.2022.2286

Algorithms and Complexities of Matching Variants in Covariate Balancing

Dorit S. Hochbaum, Asaf Levin, Xu Rao

Data and Decision Sciences

Technion - Israel Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.

Original language	English
Pages (from-to)	1800-1814
Number of pages	15
Journal	Operations Research
Volume	71
Issue number	5
DOIs	https://doi.org/10.1287/opre.2022.2286
State	Published - 1 Sep 2023

Keywords

algorithms
complexity
covariate balance
matching
observational studies

All Science Journal Classification (ASJC) codes

Computer Science Applications
Management Science and Operations Research

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10.1287/opre.2022.2286

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title = "Algorithms and Complexities of Matching Variants in Covariate Balancing",

abstract = "Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.",

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AU - Levin, Asaf

AU - Rao, Xu

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Y1 - 2023/9/1

N2 - Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.

AB - Here, we study several variants of matching problems that arise in covariate balancing. Covariate balancing problems can be viewed as variants of matching, or b-matching, with global side constraints. We present here a comprehensive complexity study of the covariate balancing problems providing polynomial time algorithms, or a proof of NP-hardness. The polynomial time algorithms described are mostly combinatorial and rely on network flow techniques. In addition, we present several fixed-parameter tractable results for problems where the number of covariates and the number of levels of each covariate are seen as a parameter.

KW - algorithms

KW - complexity

KW - covariate balance

KW - matching

KW - observational studies

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DO - 10.1287/opre.2022.2286

M3 - مقالة

SN - 0030-364X

VL - 71

SP - 1800

EP - 1814

JO - Operations Research

JF - Operations Research

IS - 5

ER -

Algorithms and Complexities of Matching Variants in Covariate Balancing

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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