Entropy Balancing

Entropy Balancing is a statistical method implemented as both an R package and a Stata routine, designed for reweighting data to achieve covariate balance in observational studies.

The method is based on the approaches developed in Hainmueller (2012) and Hainmueller and Xu (2013) , and it won the Warren Miller Award from the Society of Political Methodology in 2020.

Entropy Balancing for R

Entropy Balancing for Stata

Explainer for R and Stata

References

Journal Articles

Political Analysis

Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies

Jens Hainmueller

Political Analysis, 2012

Miller Prize DOI Bib HTML PDF

Miller Prize for best work appearing in Political Analysis the preceding year (https://polmeth.org/miller-prize).

@article{hainmueller2012entropy,
  title = {Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies},
  author = {Hainmueller, Jens},
  journal = {Political Analysis},
  volume = {20},
  number = {1},
  pages = {25--46},
  year = {2012},
  publisher = {Cambridge University Press},
  doi = {10.1093/pan/mpr025},
  url = {https://doi.org/10.1093/pan/mpr025},
}

JSS

Ebalance: A Stata package for entropy balancing

Jens Hainmueller, and Yiqing Xu

Journal of Statistical Software, 2013

DOI Bib HTML PDF

@article{hainmueller2013ebalance,
  title = {Ebalance: A Stata package for entropy balancing},
  author = {Hainmueller, Jens and Xu, Yiqing},
  journal = {Journal of Statistical Software},
  volume = {54},
  number = {7},
  year = {2013},
  doi = {10.18637/jss.v054.i07},
  url = {https://doi.org/10.18637/jss.v054.i07},
}