match2C: Match One Sample using Two Criteria

Multivariate matching in observational studies typically has two goals: 1. to construct treated and control groups that have similar distribution of observed covariates and 2. to produce matched pairs or sets that are homogeneous in a few priority variables. This packages implements a network-flow-based method built around a tripartite graph that can simultaneously achieve both goals. The package also implements a template matching algorithm using a variant of the tripartite graph design. A brief description of the workflow and some examples are given in the vignette. A more elaborated tutorial can be found at <https://www.researchgate.net/publication/359513837_Tutorial_for_R_Package_match2C>.

Version: 1.2.3
Imports: ggplot2, mvnfast, rcbalance, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: dplyr, knitr, mvtnorm, RItools, rmarkdown
Published: 2022-03-28
Author: Bo Zhang [aut, cre]
Maintainer: Bo Zhang <bozhan at wharton.upenn.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
In views: CausalInference
CRAN checks: match2C results

Documentation:

Reference manual: match2C.pdf
Vignettes: Tutorial for R Package match2C

Downloads:

Package source: match2C_1.2.3.tar.gz
Windows binaries: r-devel: match2C_1.2.3.zip, r-release: match2C_1.2.3.zip, r-oldrel: match2C_1.2.3.zip
macOS binaries: r-release (arm64): match2C_1.2.3.tgz, r-oldrel (arm64): match2C_1.2.3.tgz, r-release (x86_64): match2C_1.2.3.tgz, r-oldrel (x86_64): match2C_1.2.3.tgz
Old sources: match2C archive

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