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Spatial Coarsened Exact Matching (Spatial CEM)×Pemadanan Skor Kecenderungan Ruang×
BidangInferens KausalInferens Kausal
KeluargaRegression modelRegression model
Tahun asal2012 (CEM foundation); spatial extension in applied literature 2015-present2000s
PengasasIacus, King & Porro (CEM foundation, 2012); extended to spatial contexts by applied spatial econometriciansExtension of Rosenbaum & Rubin (1983) PSM to spatial settings; spatial adaptation developed in applied econometrics and epidemiology literature from the 2000s onward
JenisQuasi-experimental matching estimator with spatial covariatesQuasi-experimental matching estimator
Sumber perintisIacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. DOI ↗
AliasSpatial CEM, Geographic CEM, Spatial exact matching, CEM with spatial covariatesSpatial PSM, Geospatial PSM, Spatially-adjusted propensity score matching, Geographic propensity score matching
Berkaitan66
RingkasanSpatial Coarsened Exact Matching applies the Coarsened Exact Matching framework to study designs involving geographic units — neighbourhoods, census tracts, municipalities, or grid cells. Covariates are coarsened into discrete bins and units are matched exactly on those bins, with spatial attributes (location, adjacency, geographic characteristics) incorporated as matching dimensions to control for spatial confounding.Spatial Propensity Score Matching (Spatial PSM) extends the classic propensity score matching framework to settings where units are embedded in geographic space and treatment assignment or outcomes may be spatially correlated. By incorporating spatial covariates and adjacency structure into the propensity model and matching procedure, it produces causal estimates that account for geographic confounding and spillover effects.
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ScholarGateBandingkan kaedah: Spatial Coarsened Exact Matching · Spatial Propensity Score Matching. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare