%CEM is a SAS macro which allows researchers to perform the recently introduced Coarsened Exact Matching (CEM) technique. CEM is a non-parametric matching method to avoid the confounding influence of pre-treatment control variables directly improving causal inference in quasi experimental studies. The %CEM macro introduces a completely automated process wich allows SAS users to perform an exact matching over massive data. Several matching strategies automatically test the population’s imbalance providing the optimal variables binning an associated L1 imbalance measure. An empirical application estimating the causal effect of regional health systems on the intra-hospital mortality using multiple administrative datasets from a large regional database completes the paper.

Verzillo, S., Berta, P., Bossi, M. (2013). \% CEM: A SAS Macro to perform Coarsened Exact Matching [Working paper].

\% CEM: A SAS Macro to perform Coarsened Exact Matching

BERTA, PAOLO;
2013

Abstract

%CEM is a SAS macro which allows researchers to perform the recently introduced Coarsened Exact Matching (CEM) technique. CEM is a non-parametric matching method to avoid the confounding influence of pre-treatment control variables directly improving causal inference in quasi experimental studies. The %CEM macro introduces a completely automated process wich allows SAS users to perform an exact matching over massive data. Several matching strategies automatically test the population’s imbalance providing the optimal variables binning an associated L1 imbalance measure. An empirical application estimating the causal effect of regional health systems on the intra-hospital mortality using multiple administrative datasets from a large regional database completes the paper.
Working paper
Coarsened Exact Matching, Causal inference, SAS, SAS/IML
English
2013
60
60
Verzillo, S., Berta, P., Bossi, M. (2013). \% CEM: A SAS Macro to perform Coarsened Exact Matching [Working paper].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/60452
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