%CEM: a SAS macro to perform coarsened exact matching. Issue 2 (22nd January 2017)

• Record Type: Journal Article
• Authors: Berta, Paolo; Bossi, Matteo; Verzillo, Stefano
• Is Part Of: Journal of statistical computation and simulation. Volume 87:Issue 2(2017)
• Page Start: 227
• Page End: 238
• Publication Date: 2017-01-22
• Subjects: Coarsened exact matching -- causal inference -- SAS -- matching frontier; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2016.1203433
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: In this paper we introduce %CEM, a macro package allowing researchers to automatically perform coarsened exact matching (CEM) in SAS environment. CEM is a non-parametric matching method widely used by researchers to avoid the confounding influence of pre-treatment control variables to improve causal inference in quasi-experimental studies. %CEM introduces a completely automated process which allows SAS users to efficiently perform CEM in fields in which large data sets are common and where SAS is the most popular statistical tool. In addition, such a macro may be used to test several coarsening combinations of numeric variables. This option also provides a visual representation of the matching frontier, thus enabling researchers to select the optimal setting which takes into account both the L 1 imbalance and the percentage of matched units. The paper concludes with an empirical application comparing computational performance and results obtained using alternative available software (SAS, R and STATA) using multiple administrative data sets from a large regional database.