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triplesmatch

The goal of triplesmatch is to attain excellent covariate balance by matching two treated units and one control unit or vice versa within strata. Using such triples, as opposed to also allowing pairs of treated and control units, allows easier interpretation of the two possible weights of observations and better insensitivity to unmeasured bias in the test statistic. Using triples instead of matching in a fixed 1:2 or 2:1 ratio allows for the match to be feasible in more situations.

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/. The 'Gurobi' commercial optimization software is required to use the two functions ``infsentrip()andtriplesIP()`. These functions are not essential to the function of this package. The 'gurobi' R package can be installed following the instructions at https://www.gurobi.com/documentation/9.1/refman/ins_the_r_package.html.

Installation

You can install the release version of optrefine from CRAN with:

install.packages("triplesmatch")

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Version

Install

install.packages('triplesmatch')

Monthly Downloads

124

Version

1.1.0

License

GPL-3

Maintainer

Katherine Brumberg

Last Published

July 29th, 2024

Functions in triplesmatch (1.1.0)

infsentrip

Sensitivity analysis for triples matches informed by tests for unmeasured bias
triples_st

Create a triples match for a single stratum
boxplot_matches

Series of boxplots for a given variable characterizing the triples match
triples

Create a triples match
triplesIP

Integer program for finding optimal triples match
boxplot_diffs

Boxplots of pairwise differences in triples match
make_bal_tab

Make covariate balance table
aberrantscoreslong

Convert outcome to aberrant ranks
cut_quant

Create strata based on quantiles of a score
dist_mahal

Make Mahalanobis distance matrix
formattrip

Formats the triples match for input to other functions
aberrantscores

Convert outcome to aberrant ranks
sentrip

Sensitivity analysis for a triples match in an observational study