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>.
Package details |
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Author | Bo Zhang [aut, cre] |
Maintainer | Bo Zhang <bzhang3@fredhutch.org> |
License | MIT + file LICENSE |
Version | 1.2.4 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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