Implementing double-robust estimators of causal effects
| dc.creator | Emsley, Richard | |
| dc.creator | Lunt, Mark | |
| dc.creator | Pickles, Andrew | |
| dc.creator | Dunn, Graham | |
| dc.date | 2017-04-01T19:37:02Z | |
| dc.date.accessioned | 2026-07-09T06:01:12Z | |
| dc.description | 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. | |
| dc.identifier | Other:st0149 | |
| dc.identifier | doi:10.22004/ag.econ.122597 | |
| dc.identifier | https://ageconsearch.umn.edu/record/122597/files/sjart_st0149.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/122597 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/571303 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/122597 | |
| dc.title | Implementing double-robust estimators of causal effects | |
| dc.type | Text |