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designmatch (version 0.2.0)

Construction of Optimally Matched Samples for Randomized Experiments and Observational Studies that are Balanced and Representative by Design

Description

Includes functions for the construction of matched samples that are balanced and representative by design. Among others, these functions can be used for matching in observational studies with treated and control units, with cases and controls, in related settings with instrumental variables, and in discontinuity designs. Also, they can be used for the design of randomized experiments, for example, for matching before randomization. By default, 'designmatch' uses the 'GLPK' optimization solver, but its performance is greatly enhanced by the 'Gurobi' optimization solver and its associated R interface. For their installation, please follow the instructions at http://user.gurobi.com/download/gurobi-optimizer and http://www.gurobi.com/documentation/6.5/refman/r_api_overview.html. We have also included directions in the gurobi_installation file in the inst folder.

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Version

Install

install.packages('designmatch')

Monthly Downloads

87

Version

0.2.0

License

GPL-2 | GPL-3

Maintainer

Jose Zubizarreta

Last Published

August 11th, 2016

Functions in designmatch (0.2.0)

germancities

Data from German cities before and after the Second World War
finetab

Tabulate the marginal distribution of a nominal covariate after matching
absstddif

loveplot

Love plot for assessing covariate balance
designmatch-package

ecdfplot

Empirical cumulative distribution function plot for assessing covariate balance
lalonde

Lalonde data set
meantab

Tabulate means of covariates after matching
distmat

Build a rank-based Mahalanobis distance matrix
bmatch

Optimal bipartite matching in observational studies
pairsplot

Pairs plot for visualizing matched pairs
nmatch