方法证据记录
Heterogeneous Treatment Effect Coarsened Exact Matching
Heterogeneous treatment effect coarsened exact matching (HTE-CEM) extends the coarsened exact matching framework to estimate how treatment effects vary across subgroups or individual characteristics. After CEM creates balanced strata by coarsening continuous covariates into bins and exactly matching units within each bin, conditional average treatment effects (CATEs) are computed within or across these strata, revealing where treatment works, for whom, and by how much.
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。
Heterogeneous Treatment Effect Estimation via Coarsened Exact Matching
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
- Imai, K., & Ratkovic, M. (2013). Estimating treatment effect heterogeneity in randomized program evaluation. Annals of Applied Statistics, 7(1), 443-470. · DOI 10.1214/12-AOAS593
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