Propensity score matching is commonly used to draw causal inference from
observational survival data. However, there is no gold standard approach to
analyze survival data after propensity score matching, and variance estimation
after matching is 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.