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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.

copied from cf-post-staging / r-optmatch
Type Size Name Uploaded Downloads Labels
conda 997.6 kB | win-64/r-optmatch-0.10.7-r41ha856d6a_0.conda  1 year and 10 months ago 488 main
conda 1007.3 kB | osx-64/r-optmatch-0.10.7-r43h64b2c41_0.conda  1 year and 10 months ago 403 main
conda 1003.2 kB | osx-64/r-optmatch-0.10.7-r42h64b2c41_0.conda  1 year and 10 months ago 367 main
conda 1016.0 kB | linux-64/r-optmatch-0.10.7-r42ha503ecb_0.conda  1 year and 10 months ago 1894 main
conda 1020.5 kB | linux-64/r-optmatch-0.10.7-r43ha503ecb_0.conda  1 year and 10 months ago 1975 main

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