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Bajezijansko grubo precizno uparivanje×Bejzijansko uparivanje skora sklonosti×
OblastKauzalno zaključivanjeKauzalno zaključivanje
PorodicaRegression modelRegression model
Godina nastanka2011-20122012
TvoracIacus, King & Porro (CEM framework, 2012); Bayesian extensions by Hill and subsequent authorsKaplan & Chen (2012); foundational PSM by Rosenbaum & Rubin (1983)
TipQuasi-experimental matching with Bayesian inferenceBayesian causal inference / matching
Temeljni izvorIacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗Kaplan, D., & Chen, J. (2012). A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study. Psychometrika, 77(3), 581-609. DOI ↗
Drugi naziviBayesian CEM, BCEM, Bayesian monotonic imbalance bounding matchingBayesian PSM, BPSM, Bayesian matching estimator, Bayesian propensity weighting
Srodne66
SažetakBayesian 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.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.
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ScholarGateUporedite metode: Bayesian Coarsened Exact Matching · Bayesian Propensity Score Matching. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare