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Zhrubnuté presné párovanie (CEM)×Odhadovač založený na párovaní×
OdborKauzálna inferenciaKauzálna inferencia
RodinaRegression modelRegression model
Rok vzniku2011-20121973
TvorcaIacus, King, & PorroRubin (1973); large-sample theory by Abadie & Imbens (2006)
TypMatching / causal inferenceNonparametric matching / causal inference
Pôvodný zdrojIacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗
Ďalšie názvyCEM, coarsened matching, monotonic imbalance bounding matchingnearest-neighbor matching, NNM, matching on covariates, covariate matching
Príbuzné66
ZhrnutieCoarsened 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.The matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome.
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ScholarGatePorovnať metódy: Coarsened Exact Matching · Matching Estimator. Získané 2026-06-19 z https://scholargate.app/sk/compare