方法证据记录
Propensity Score Matching
Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Propensity Score Matching and Weighting
分类方法记录 · process-pipeline / research-statistics
- Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. · DOI 10.1093/biomet/70.1.41
- Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding. Multivariate Behavioral Research, 46(3), 399–424. · DOI 10.1080/00273171.2011.568786
- Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66(5), 688–701. · DOI 10.1037/h0037350
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