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 |
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