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The Stata Journal
Volume 8 Number 3: pp. 334-353



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Implementing double-robust estimators of causal effects

Richard Emsley
Biostatistics, Health Methodology Research Group
The University of Manchester, UK
richard.emsley@manchester.ac.uk
Mark Lunt
Arthritis Research Campaign Epidemiology Unit
The University of Manchester, UK
Andrew Pickles
Biostatistics, Health Methodology Research Group
The University of Manchester, UK
Graham Dunn
Biostatistics, Health Methodology Research Group
The University of Manchester, UK
Abstract.   This article describes the implementation of a double-robust estimator for pretest–posttest studies (Lunceford and Davidian, 2004, Statistics in Medicine 23: 2937–2960) and presents a new Stata command (dr) that carries out the procedure. A double-robust estimator gives the analyst two opportunities for obtaining unbiased inference when adjusting for selection effects such as confounding by allowing for different forms of model misspecification; a double-robust estimator also can offer increased efficiency when all the models are correctly specified. We demonstrate the results with a Monte Carlo simulation study, and we show how to implement the double-robust estimator on a single simulated dataset, both manually and by using the dr command.
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