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Cited by 1,113

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

ebalance : A Stata Package for Entropy Balancing

Open access
Hainmueller, Jens, Xu, Yiqing·2013·Journal of Statistical Software
DOI 10.18637/jss.v054.i07
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Abstract

The Stata package ebalance implements entropy balancing, a multivariate reweighting method described in Hainmueller (2011) that allows users to reweight a dataset such that the covariate distributions in the reweighted data satisfy a set of specied 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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Metadata

Authors
Hainmueller, J., & Xu, Y.
Venue
Journal of Statistical Software
Publisher
Foundation for Open Access Statistic
Published
2013
Volume
54
Issue
7
ISSN
1548-7660 (ISSN-L)
DOI
10.18637/jss.v054.i07
OpenAlex
W3124410553
Cited by
1,113
References
2
FWCI
3.89
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: ebalance : A Stata Package for Entropy Balancing. https://app.cochat.ai/papers/10.18637/jss.v054.i07
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Hainmueller, J., & Xu, Y. (2013). ebalance : A Stata Package for Entropy Balancing. Journal of Statistical Software. https://doi.org/10.18637/jss.v054.i07

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.