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Implementing double-robust estimators of causal effects 31
Emsley, Richard; Lunt, Mark; Pickles, Andrew; Dunn, Graham.
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.
Tipo: Article Palavras-chave: Dr; Double-robust estimators; Causal models; Confounding; Inverse probability of treatment weights; Propensity score; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/122597
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