So sánh phương pháp

	Ghép Xu hướng Xuất hiện Bayes (Bayesian Propensity Score Matching)	Ghép Chính xác Tinh chỉnh (CEM)
Lĩnh vực	Suy luận nhân quả	Suy luận nhân quả
Họ	Regression model	Regression model
Năm ra đời	2012	2011-2012
Người khởi xướng	Kaplan & Chen (2012); foundational PSM by Rosenbaum & Rubin (1983)	Iacus, King, & Porro
Loại	Bayesian causal inference / matching	Matching / causal inference
Công trình gốc	Kaplan, D., & Chen, J. (2012). A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study. Psychometrika, 77(3), 581-609.	Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24.
Tên gọi khác	Bayesian PSM, BPSM, Bayesian matching estimator, Bayesian propensity weighting	CEM, coarsened matching, monotonic imbalance bounding matching
Liên quan	6	6
Tóm tắt	Bayesian Propensity Score Matching (Bayesian PSM) extends classical propensity score matching by placing a prior distribution over the propensity model parameters and propagating posterior uncertainty through the matching and outcome stages. Introduced formally by Kaplan and Chen (2012), it offers a principled account of estimation uncertainty that frequentist matching commonly ignores, and allows incorporation of substantive prior knowledge about treatment selection.	Coarsened Exact Matching is a preprocessing method that achieves covariate balance by temporarily coarsening continuous variables into bins, exactly matching treated and control units within those bins, and then discarding all unmatched units. Introduced by Iacus, King, and Porro (2011, 2012), it bounds imbalance on each covariate independently, yielding a matched sample on which any estimator can be applied without relying on a propensity score model.