Causal inference of hazard ratio based on propensity score matching
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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.
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