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.