Affiliation:
1. Eli Lilly and Company Indianapolis Indiana USA
2. Department of Statistics North Carolina State University Raleigh North Carolina USA
Abstract
Propensity score matching is commonly used to draw causal inference from observational survival data. However, its asymptotic properties have yet to be established, and variance estimation is still open to debate. We derive the statistical properties of the propensity score matching estimator of the marginal causal hazard ratio based on matching with replacement and a fixed number of matches. We also propose a double‐resampling technique for variance estimation that takes into account the uncertainty due to propensity score estimation prior to matching.
Funder
National Science Foundation of Sri Lanka
National Institutes of Health