Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the bigmatch package are optcal() to find the optimal caliper and nfmatch() to find a near-fine balance match with a caliper.
Glover, F. (1967).  <DOI:10.1002/nav.3800140304>.
Lipski, W., Jr, and Preparata, F. P. (1981). <DOI:10.1007/BF00264533>.
Rosenbaum, P.R. (1989). <DOI:10.1080/01621459.1989.10478868>.
Yang, D., Small, D. S., Silber, J. H., and Rosenbaum, P. R. (2012). <DOI:10.1111/j.1541-0420.2011.01691.x>.

Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the 'bigmatch' package are optcal() to find the optimal caliper, optconstant() to find the optimal number of nearest neighbors and nfmatch() to find a near-fine balance match with a caliper and a restriction on number of nearest neighbors.
Glover, F. (1967).  <DOI:10.1002/nav.3800140304>.
Lipski, W., Jr, and Preparata, F. P. (1981). <DOI:10.1007/BF00264533>.
Rosenbaum, P.R. (1989). <DOI:10.1080/01621459.1989.10478868>.
Yang, D., Small, D. S., Silber, J. H., and Rosenbaum, P. R. (2012). <DOI:10.1111/j.1541-0420.2011.01691.x>.

Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the 'bigmatch' package are optcal() to find the optimal caliper, optconstant() to find the optimal number of nearest neighbors, and nfmatch() to find a near-fine balance match with a caliper and a restriction on the number of nearest neighbors.
Yu, R., Silber, J. H., and Rosenbaum, P. R. (2020). <DOI:10.1214/19-sts699>.
The optmatch package, which is useful for running many of the
provided functions, may be downloaded from Github at
<https://github.com/markmfredrickson/optmatch> if not available
on CRAN. The rrelaxiv package, which provides an alternative
solver for the underlying network flow problems, carries an
academic license and is not available on CRAN, but may be
downloaded from Github at
<https://github.com/josherrickson/rrelaxiv/>.