ebalance: A Stata Package for Entropy Balancing

The Stata package ebalance implements entropy balancing, a multivariate reweighting method described in Hainmueller (2012 ) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of specified moment conditions. This can be useful to create...

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Main Authors: Hainmueller, Jens, Su, Yiqing, Xu, Yiqing
Other Authors: Massachusetts Institute of Technology. Department of Political Science
Format: Article
Language:en_US
Published: UCLA Statistics/American Statistical Association 2014
Online Access:http://hdl.handle.net/1721.1/89819
https://orcid.org/0000-0003-2041-6671
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author Hainmueller, Jens
Su, Yiqing
Xu, Yiqing
author2 Massachusetts Institute of Technology. Department of Political Science
author_facet Massachusetts Institute of Technology. Department of Political Science
Hainmueller, Jens
Su, Yiqing
Xu, Yiqing
author_sort Hainmueller, Jens
collection MIT
description The Stata package ebalance implements entropy balancing, a multivariate reweighting method described in Hainmueller (2012 ) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of specified moment conditions. This can be useful to create balanced samples in observational studies with a binary treatment where the control group data can be reweighted to match the covariate moments in the treatment group. Entropy balancing can also be used to reweight a survey sample to known characteristics from a target population.
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spelling mit-1721.1/898192022-09-29T10:04:49Z ebalance: A Stata Package for Entropy Balancing Hainmueller, Jens Su, Yiqing Xu, Yiqing Massachusetts Institute of Technology. Department of Political Science Hainmueller, Jens Xu, Yiqing The Stata package ebalance implements entropy balancing, a multivariate reweighting method described in Hainmueller (2012 ) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of specified moment conditions. This can be useful to create balanced samples in observational studies with a binary treatment where the control group data can be reweighted to match the covariate moments in the treatment group. Entropy balancing can also be used to reweight a survey sample to known characteristics from a target population. 2014-09-18T18:38:45Z 2014-09-18T18:38:45Z 2012-08 2011-10 Article http://purl.org/eprint/type/JournalArticle 1548-7660 http://hdl.handle.net/1721.1/89819 Hainmueller, Jens, and Yiqing Xu. "ebalance: A Stata Package for Entropy Balancing." Journal of Statistical Software, Vol. 54, Issue 7 (Sept 2013). https://orcid.org/0000-0003-2041-6671 en_US http://www.jstatsoft.org/v54/i07 Journal of Statistical Software Creative Commons Attribution http://creativecommons.org/licenses/by/3.0/ application/pdf UCLA Statistics/American Statistical Association UCLA Statistics/American Statistical Association
spellingShingle Hainmueller, Jens
Su, Yiqing
Xu, Yiqing
ebalance: A Stata Package for Entropy Balancing
title ebalance: A Stata Package for Entropy Balancing
title_full ebalance: A Stata Package for Entropy Balancing
title_fullStr ebalance: A Stata Package for Entropy Balancing
title_full_unstemmed ebalance: A Stata Package for Entropy Balancing
title_short ebalance: A Stata Package for Entropy Balancing
title_sort ebalance a stata package for entropy balancing
url http://hdl.handle.net/1721.1/89819
https://orcid.org/0000-0003-2041-6671
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