Epidemiol Rev. 2021 Jun 10; doi: 10.1093/epirev/mxab003. Epub 2021 Jun 10.

Matching Methods for Confounder Adjustment: An Addition to the Epidemiologist's Toolbox.

Epidemiologic reviews

Noah Greifer, Elizabeth A Stuart

PMID: 34109972 DOI: 10.1093/epirev/mxab003

Abstract

Propensity score weighting and outcome regression are popular ways to adjust for observed confounders in epidemiological research. Here, we provide an introduction to matching methods, which serve the same purpose but can offer advantages in robustness and performance. A key difference between matching and weighting methods is that matching methods do not directly rely on the propensity score and so are less sensitive to its misspecification or to the presence of extreme values. Matching methods offer many options for customization, which allow a researcher to incorporate substantive knowledge and carefully manage bias/variance trade-offs in estimating the effects of nonrandomized exposures. We review these options and their implications, providing guidance for their use, and comparison with weighting methods. Because of their potential advantages over other methods, matching methods should have their place in an epidemiologist's methodological toolbox.

© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: [email protected].

Keywords: epidemiologic methods; propensity score

Publication Types

• Journal Article