Evaluating the Use of Bootstrapping in Cohort Studies Conducted with 1:1 Propensity Score Matching — A Plasmode Simulation Study

Basic Details
Wednesday, April 24, 2019

Bootstrapping can account for uncertainty in propensity score (PS) estimation and matching processes in 1:1 PS‐matched cohort studies. While theory suggests that the classical bootstrap can fail to produce proper coverage, practical impact of this theoretical limitation in settings typical to pharmacoepidemiology is not well studied. In a plasmode‐based simulation study, the authors compared performance of the standard parametric approach, which ignores uncertainty in PS estimation and matching, with two bootstrapping methods. 


Rishi J. Desai, Richard Wyss, Younathan Abdia, Sengwee Toh, Margaret Johnson, Hana Lee, Sara Karami, Jacqueline M. Major, Michael Nguyen, Shirley V. Wang, Jessica M. Franklin, Joshua J. Gagne

Corresponding Author

Rishi J. Desai, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Suite 3030‐R, Boston, MA 02120, USA. Email: rdesai@bwh.harvard.edu