Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen' and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Version: 0.10.8 Depends: R (≥ 3.5.0) Imports: Rcpp, dplyr, stats, tibble, methods, graphics, rlemon LinkingTo: Rcpp Suggests: RItools, boot, biglm, survey, testthat (≥ 0.11.0), roxygen2, brglm, arm, knitr, rmarkdown, markdown, pander, xtable, rrelaxiv, magrittr Enhances: CBPS, haven Published: 2024-09-19 DOI: 10.32614/CRAN.package.optmatch Author: Ben Hansen [aut], Mark Fredrickson [aut], Josh Errickson [cre, aut], Josh Buckner [aut], Adam Rauh [ctb] Maintainer: Josh Errickson <jerrick at umich.edu> BugReports: https://github.com/markmfredrickson/optmatch/issues License: MIT + file LICENSE URL: http://optmat.ch, https://github.com/markmfredrickson/optmatch NeedsCompilation: yes Additional_repositories: https://errickson.net/rrelaxiv Citation: optmatch citation info Materials: NEWS In views: CausalInference, Optimization CRAN checks: optmatch resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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