Study Design / Propensity Score Methods

Selected Papers

  • Hansford, H.J., Cashin, A.G., Jones, M.D., Swanson, S.J., Islam, N., Douglas, S.R.G., Rizzo, R.R.N., Devonshire, J.J., Williams, S.A., Dahabreh, I.J., Dickerman, B.A., Egger, M., Garcia-Albeniz, X., Golub, R.M., Lodi, S., Moreno-Betancur, M., Pearson, S-A., Schneeweiss, S., Sterne, J.A.C., Sharp, M.K., Stuart, E.A., Hernan, M.A., Lee, H., McAuley, J.H. (2023). Development of the TrAnsparent ReportinG of observational studies emulating a target trial (TARGET) guideline. BMJ Open, 13(9), e074626-e074626. Article link

  • Hong, H., Aaby, D. A., Siddique, J., & Stuart, E. A. (2019). Propensity score–based estimators with multiple error-prone covariates. American journal of epidemiology, 188(1), 222-230. Article link

  • Kohler, U., Kreuter, F., & Stuart, E. A. (2019). Nonprobability sampling and causal analysis. Annual review of statistics and its application, 6(1), 149-172. Pubmed link

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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. 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 ↩︎

Last updated on Aug 6, 2024