SVMMatch: Causal Effect Estimation and Diagnostics with Support Vector Machines

Causal effect estimation in observational data often requires identifying a set of untreated observations that are comparable to some treated group of interest. This package provides a suite of functions for identifying such a set of observations and for implementing standard and new diagnostics tools. The primary function, svmmatch(), uses support vector machines to identify a region of common support between treatment and control groups. A sensitivity analysis, balance checking, and assessment of the region of overlap between treated and control groups is included. The Bayesian implementation allows for recovery of uncertainty estimates for the treatment effect and all other parameters.

Version: 1.1
Depends: R (≥ 3.0.2)
Imports: Rcpp (≥ 0.11.0)
LinkingTo: Rcpp, RcppArmadillo
Published: 2015-02-08
Author: Marc Ratkovic
Maintainer: Marc Ratkovic <ratkovic at princeton.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: SVMMatch results

Downloads:

Reference manual: SVMMatch.pdf
Package source: SVMMatch_1.1.tar.gz
Windows binaries: r-devel: SVMMatch_1.1.zip, r-release: SVMMatch_1.1.zip, r-oldrel: SVMMatch_1.1.zip
OS X Mavericks binaries: r-release: SVMMatch_1.1.tgz, r-oldrel: SVMMatch_1.1.tgz
Old sources: SVMMatch archive

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