Can we plan the design and analysis of observational studies to better distinguish effects caused by a treatment from unmeasured confounding that remains after adjustment for measured covariates? The answer is "yes". Design sensitivity is a quantitative measure of our ability of to distinguish a casual effect from unmeasured confounding. We prefer designs and methods with larger design sensitivities.
Rosenbaum PR. Design sensitivity in observational studies. Biometrika. 2004 Mar 1;91(1):153-64. In JSTOR: www.jstor.org/stable/20441085 https://doi.org/10.1093/biomet/91.1.153
Rosenbaum PR. Heterogeneity and causality: Unit heterogeneity and design sensitivity in observational studies. American Statistician. 2005 May 1;59(2):147-52. In JSTOR: www.jstor.org/stable/27643648 https://doi.org/10.1198/000313005X42831
Heller R, Rosenbaum PR, Small DS. Split samples and design sensitivity in observational studies. Journal of the American Statistical Association. 2009 Sep 1;104(487):1090-101. In JSTOR: www.jstor.org/stable/40592278 https://doi.org/10.1198/jasa.2009.tm08338
Rosenbaum PR. Design sensitivity and efficiency in observational studies. Journal of the American Statistical Association. 2010 Jun 1;105(490):692-702. In JSTOR: www.jstor.org/stable/29747075 https://doi.org/10.1198/jasa.2010.tm09570
Rosenbaum PR. A new U-statistic with superior design sensitivity in matched observational studies. Biometrics. 2011 Sep;67(3):1017-27. In JSTOR: www.jstor.org/stable/41242550 https://doi.org/10.1111/j.1541-0420.2010.01535.x
Rosenbaum PR. An Exact Adaptive Test With Superior Design Sensitivity in an Observational Study of Treatments for Ovarian Cancer. Annals of Applied Statistics. 2012 Jan 1;6(351):83-105. In JSTOR: www.jstor.org/stable/41713442 Open access at ProjectEuclid https://doi.org/10.1214/11-AOAS508
Rosenbaum PR. Testing one hypothesis twice in observational studies. Biometrika. 2012 Dec 1;99(4):763-74. In JSTOR: www.jstor.org/stable/41720732 https://doi.org/10.1093/biomet/ass032
Hsu JY, Small DS, Rosenbaum PR. Effect modification and design sensitivity in observational studies. Journal of the American Statistical Association. 2013 Mar 1;108(501):135-48. In JSTOR: www.jstor.org/stable/23427517 https://doi.org/10.1080/01621459.2012.742018
Zubizarreta JR, Cerdá M, Rosenbaum PR. Effect of the 2010 Chilean earthquake on posttraumatic stress: Reducing sensitivity to unmeasured bias through study design. Epidemiology. 2013 Jan 1;24(1):79-87. Open access via the US National Library of Medicine: https://pmc.ncbi.nlm.nih.gov/articles/PMC3580201/ https://doi.org/10.1097/EDE.0b013e318277367e
Rosenbaum PR. Impact of multiple matched controls on design sensitivity in observational studies. Biometrics. 2013 Mar;69(1):118-27. In JSTOR: www.jstor.org/stable/41806073 https://doi.org/10.1111/j.1541-0420.2012.01821.x
Rosenbaum PR. Weighted M-statistics with superior design sensitivity in matched observational studies with multiple controls. Journal of the American Statistical Association. 2014 Jul 3;109(507):1145-58. In JSTOR: www.jstor.org/stable/24247442 https://doi.org/10.1080/01621459.2013.879261
Rosenbaum PR. A conditioning tactic that increases design sensitivity in observational block designs. Journal of the Royal Statistical Society Series B. 2025 Sep;87(4):1085-99. https://doi.org/10.1093/jrsssb/qkaf007