if you use CEM and turn off the calculation of L1, its very fast and can
deal with very large data sets.
Gary
--
*Gary King* - Albert J. Weatherhead III University Professor - Director,
IQSS - Harvard University
GKing.Harvard.edu <http://gking.harvard.edu/> - King(a)Harvard.edu -
@kinggary<http://twitter.com/kinggary>- 617-500-7570 - Asst 495-9271 -
Fax 812-8581
On Mon, Feb 27, 2012 at 12:14 PM, Donny Baum <donnybaum(a)gmail.com> wrote:
Has anyone come across problems of performance using
MatchIt with large
datasets? I am trying to perform nearest neighbor matching with 10
subclassifications on a sample of 400,000 (50,000 treatment cases, 350,00
untreated) with about 25 covariates. I was able to get one round of
successful results after about 8 hours of waiting for R to produce the
output. Is this typical of using MatchIt with large data? Is there any way
to increase the speed or otherwise work around this?
Any help would be great.
Cheers,
Don Baum
--
Don Baum
Ph.D. Candidate/ Graduate Assistant
Comparative and International Development Education
Educational Policy and Administration
University of Minnesota
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