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bigmatch (version 0.6.4)

Making Optimal Matching Size-Scalable Using Optimal Calipers

Description

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). .

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Install

install.packages('bigmatch')

Monthly Downloads

287

Version

0.6.4

License

MIT + file LICENSE

Maintainer

Ruoqi Yu

Last Published

August 11th, 2022

Functions in bigmatch (0.6.4)

findexact

Build an exact match variable given a matrix of covariates ordered by the user according to their importance.
edgenum

Computes the number of edges in the reduced bipartite.
optconstant

Finds the optimal constant.
nearfine

Minimum-distance near-fine matching.
optcal

Finds the optimal caliper width.
glover

Maximum matching in a convex bipartite graph.
nfmatch

Minimum-distance near-fine matching.
nh0506

Smoking and homocysteine levels in NHANES 2005-2006.
check

Check SMDs of the matched data set.
netfine

Optimal near-fine match from a distance matrix.
smahal

Creates a robust Mahalanobis distance for matching.