方法证据记录
Bayesian Coarsened Exact Matching
Bayesian Coarsened Exact Matching (Bayesian CEM) combines the coarsening-and-exact-matching framework of Iacus, King, and Porro with Bayesian posterior inference. Covariates are discretised into coarser bins so that treated and control units can be matched exactly within those bins, and Bayesian priors are then placed on the treatment-effect parameters to produce full posterior distributions over the causal estimand rather than a single point estimate.
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。
Bayesian Coarsened Exact Matching Estimator
分类方法记录 · regression-model / causal-inference
- Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. · DOI 10.1093/pan/mpr013
- Hill, J. L. (2011). Bayesian Nonparametric Modeling for Causal Inference. Journal of Computational and Graphical Statistics, 20(1), 217-240. · DOI 10.1198/jcgs.2010.08162
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