This website is for the distribution of "Matching" which is a
Stata package for
estimating causal effects by multivariate and propensity score
matching. The package provides functions for multivariate and
propensity score matching and for finding optimal balance based on
a genetic search
algorithm Also see Genetic Optimization Using Derivatives: Theory and Application to Nonlinear Models for more information on the genetic matching algorithm. A variety of univariate and multivariate tests to
determine if balance has been obtained are also provided. These tests
can also be used to determine if an experiment or quasi-experiment is
balanced on baseline covariates.
MAKE SURE THAT YOU HAVE R INSTALLED ON YOUR COMPUTER. R can be downloaded at: http://www.r-project.org/
Intel Based Mac OS X binary package: Download: Matching_Stata_v0.1.zip Unzip the Matching_Stata_v0.1.zip file. This will create a folder called Matching_Stata_v0.1 in the local directory. Copy all of the contents of this folder (the genmatch folder, genmatch.ado, genmatch.hlp and genmatchCleanup.class) into your personal ado file (which can be found by typing personal in the Stata command line) or other ado location. This will install the genmatch.ado, genmatch.hlp and other necessary supporting files in your personal ado file.
Alternative Intel Based Mac OS X installation:
Download: Matching_Stata_v0.1.zip Copy Matching_Stata_v0.1.zip into your personal ado file (which can be found by typing personal in the Stata command line) or other ado location. Unzip the Matching_Stata_v0.1.zip file by typing unzip Matching_Stata_v0.1.zip in Terminal's command line (make sure you are in the local directory where you placed the zipped file). This will install the genmatch.ado, genmatch.hlp and other necessary supporting files in your personal ado file.
At this time the code is only developed for Intel-based Mac OS X. A Windows version is currently being developed. Please check back for updates.
The package includes the following main user exposed functions:
finds optimal balance using multivariate matching where a genetic
search algorithm determines the weight each covariate is given.
The user can choose which function of covariate balance to
optimize from a list or provide one of her own.
performs multivariate and propensity score matching.
lalonde.dta is the sample data set used in the genmatch examples.
It can also be obtained by typing:
. use http://ekhartman.berkeley.edu/stata/matching/lalonde
The package is under active development so please check back for
updates. Please cite the software as follows:
Erin Hartman and Jasjeet S. Sekhon. "Matching: Stata version of Multivariate and Propensity Score Matching Software for Causal Inference." URL: http://ekhartman.berkeley.edu/stata/matching.html
Sekhon, Jasjeet S. Forthcoming. "Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R." Journal of Statistical Software.
Also see "Alternative
Balance Metrics for Bias Reduction in Matching Methods for Causal
Inference" paper which critically reviews various ways to measure
balance. Cumulative probability distribution functions of
standardized statistics are advocated as balance metrics. Formal
hypothesis tests of balance should not be conducted as is common in
the matching literature because no measure of balance is a monotonic
function of bias and because balance should be optimized without
limit. However, descriptive measures of discrepancy ignore information
related to bias which is captured by probability distribution
functions of standardized statistics.
Significant performance enhancements were provided by Nate Begeman
(Mac OS X Performance Group at Apple). And "Matching" relies on a
modified version of the Scythe
Statistical Library developed by Andrew Martin, Kevin Quinn and
Daniel Pemstein. A modified version of the library is included in
the "Matching" package.