Uncertain Neighbors: Bayesian Propensity Score Matching For Causal Inference
不确定的近邻：用于因果推断的贝叶斯倾向得分匹配
We compare the performance of standard nearest-neighbor propensity score matching with that of an analogous Bayesian propensity score matching procedure. We show that the Bayesian approach makes better use of available information, as it makes less arbitrary decisions about which observations to drop and which ones to keep in the matched sample. We conduct a simulation study to evaluate the performance of standard and Bayesian nearest-neighbor matching when matching is done…