Doubly Robust Estimation of Causal Effects

2011/03/08 by Michele Jönsson Funk, Michele Jonsson Funk, Daniel Westreich +5 · 1,166 citations
Engineering · Mathematics · #Advanced Causal Inference Techniques #Causal inference #Computer science #Econometrics #Engineering #Estimation #Estimator #Macro #Mathematics #Outcome (game theory) #Propensity score matching #Regression #Regression analysis #Robust regression #Robust statistics #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics

paper · pdf · doi:10.1093/aje/kwq439

published in American Journal of Epidemiology 173(7), 761-767 (Oxford University Press)

openalex publication_date 2011/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Doubly robust estimation combines a form of outcome regression with a model for the exposure (i.e., the propensity score) to estimate the causal effect of an exposure on an outcome. When used individually to estimate a causal effect, both outcome regression and propensity score methods are unbiased only if the statistical model is correctly specified. The doubly robust estimator combines these 2 approaches such that only 1 of the 2 models need be correctly specified to obtain an unbiased effect estimator. In this introduction to doubly robust estimators, the authors present a conceptual overview of doubly robust estimation, a simple worked example, results from a simulation study examining performance of estimated and bootstrapped standard errors, and a discussion of the potential advantages and limitations of this method. The supplementary material for this paper, which is posted on the Journal's Web site (http://aje.oupjournals.org/), includes a demonstration of the doubly robust property (Web Appendix 1) and a description of a SAS macro (SAS Institute, Inc., Cary, North Carolina) for doubly robust estimation, available for download at http://www.unc.edu/~mfunk/dr/.

Citations

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• Treatment Effects in the Presence of Unmeasured Confounding: Dealing With Observations in the Tails of the Propensity Score Distribution--A Simulation Study
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• The central role of the propensity score in observational studies for causal effects

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Related

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