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nbpMatching (version 1.5.6)

Functions for Optimal Non-Bipartite Matching

Description

Perform non-bipartite matching and matched randomization. A "bipartite" matching utilizes two separate groups, e.g. smokers being matched to nonsmokers or cases being matched to controls. A "non-bipartite" matching creates mates from one big group, e.g. 100 hospitals being randomized for a two-arm cluster randomized trial or 5000 children who have been exposed to various levels of secondhand smoke and are being paired to form a greater exposure vs. lesser exposure comparison. At the core of a non-bipartite matching is a N x N distance matrix for N potential mates. The distance between two units expresses a measure of similarity or quality as mates (the lower the better). The 'gendistance()' and 'distancematrix()' functions assist in creating this. The 'nonbimatch()' function creates the matching that minimizes the total sum of distances between mates; hence, it is referred to as an "optimal" matching. The 'assign.grp()' function aids in performing a matched randomization. Note bipartite matching can be performed using the prevent option in 'gendistance()'.

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Install

install.packages('nbpMatching')

Monthly Downloads

396

Version

1.5.6

License

GPL (>= 2)

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Maintainer

Cole Beck

Last Published

September 25th, 2024

Functions in nbpMatching (1.5.6)

nbpMatching-internal

Internal nbpMatching objects.
fill.missing

Data Imputation
gendistance

Generate a Distance Matrix
get.sets

Get named sets of matches
nonbimatch

Nonbipartite Matching
assign.grp

Random Group Assignment
qom

Quality of Match
make.phantoms

Add Phantom Rows and Columns
distancematrix

Distance matrix
quantile,distancematrix-method

Quantile for upper-triangular values in distance matrix
subsetMatches

Subset Matches
scalar.dist

Calculate scalar distance
nbpMatching-package

Nonbipartite Matching