Integrating SAS® and R to Perform Optimal Propensity Score Matching
In studies where randomization is not possible, imbalance in baseline covariates (confounding by indication) is a fundamental concern. Propensity score matching (PSM) is a popular method to minimize this potential bias, matching individuals who received treatment to those who did not, to reduce the imbalance in pre-treatment covariate distributions.
PSM methods continue to advance, as computing resources expand. Optimal matching, which selects the set of matches that minimizes the average
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