Study Design / Propensity Score Methods

Selected Papers

  • Hong, H., Aaby, D.A., Siddique, J., and Stuart, E.A. Propensity score-based estimators with multiple error-prone covariates. American Journal of Epidemiology. [Article link](https://doi.org/10.1093/ aje/kwy210)

  • Kohler, U., Kreuter, F., and Stuart, E.A. Nonprobability sampling and causal analysis. Annual Reviews of Statistics and its Application. [Pubmed link](https://doi.org/10.1146/annurev- statistics-030718-104951)

  • Jackson, J.J., Schmid, I., and Stuart, E.A. (2017). Propensity scores in pharmacoepidemiology: Beyond the horizon. Current Epidemiology Reports. Topical collection on pharmacoepidemiology. Published online 6 November 2017. [Article link](http:// link.springer.com/article/10.1007/s40471-017-0131-y)

  • Austin, P.C. and Stuart, E.A. (2015). Optimal full matching for survival outcomes: A method that merits more widespread use. Statistics in Medicine 34(30): 3949-3967. PMCID: PMC4715723 Pubmed link

  • Stuart, E.A., Huskamp, H.A., Duckworth, K., Simmons, J., Song, Z., Chernew, M., and Barry, C.L. (2014). Using propensity scores in difference-in-differences models to estimate the effects of a policy change. Health Services & Outcomes Research Methodology 14(4): 166-182. PMCID: PMC4267761. Pubmed link

  • Leacy, F., and Stuart, E.A. (2014). On the joint use of propensity and prognostic scores in estimation of the Average Treatment Effect on the Treated: A simulation study. Statistics in Medicine 33(20): 3488-3508. DOI 10.1002/sim.6030. PMCID: PMC3995901. [Pubmed link] (http:// www.ncbi.nlm.nih.gov/pubmed/24151187)

  • DuGoff, E.H., **Schuler, M., and Stuart, E.A. (2014). Generalizing Observational Study Results: Applying Propensity Score Methods to Complex Surveys. Health Services Research 49(1): 284-303. PMCID: PMC3894255. [Pubmed link] (http://www.ncbi.nlm.nih.gov/pubmed/ 23855598)

  • Stuart, E.A., Lee, B.K., and **Leacy, F.P. (2013). Prognostic-score based balance measures for propensity score methods in comparative effectiveness research. Journal of Clinical Epidemiology 66: S84-S90. PMCID: PMC3713509. [Pubmed link] (http://www.ncbi.nlm.nih.gov/ pubmed/23849158)

  • Stuart, E.A. (2010). Matching Methods for Causal Inference: A review and a look forward. Statistical Science 25(1): 1-21. PMCID: PMC2943670. [Pubmed link] (http://www.ncbi.nlm.nih.gov/pubmed/ 20871802)

  • 1 Imai, K., King, G., and Stuart, E.A. (2008). Misunderstandings between experimentalists and observationalists about causal inference. Journal of the Royal Statistical Society, Series A 171: 481-502. Article link

  • 2 Ho, D.E., Imai, K., King, G., and Stuart, E.A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis 15(3): 199-236. Article link

  1. On All-Time Top 10 list of downloads, Social Science Research Network, Quantitative Methods: Econometrics, Polimetrics, and Statistics Section (as of April 15, 2008). Recognized as a “New Hot Paper in Economics and Business” by Thomson Reuters for being among the most cited in those fields. [Link] (http://sciencewatch.com/dr/nhp/2009/09julnhp/ 09julnhpImaiET/). As of June 26, 2010, most cited paper published in JRSS-A in 2007-2008. ↩︎

  2. Winner of Warren Miller Prize for best paper published in Volume 15 of Political Analysis. Selected as a Fast Breaking Paper in the field of Social Sciences, general, by Thomson Reuters, due to its being one of the most-cited papers in its discipline published between 2006 and 2008 [Link] (http://sciencewatch.com/dr/fbp/2008/08octfbp/08octfbpHoET/) ↩︎

Last updated on Oct 3, 2019