Implement entropy balancing

[exalate-issue-sync[bot]]

ref : https://web.stanford.edu/~jhain/Paper/PA2012.pdf R package : https://cran.r-project.org/web/packages/ebal/ebal.pdf

{code:java} entropy balancing, a data preprocessing method to achieve covariate balance in observational studies with binary treatments. Entropy balancing relies on a maximum entropy reweighting scheme that calibrates unit weights so that the reweighted treatment and control group satisfy a potentially large set of prespecified balance conditions that incorporate information about known sample moments. Entropy balancing thereby exactly adjusts inequalities in representation with respect to the first, second, and possibly higher moments of the covariate distributions. These balance improvements can reduce model dependence for the subsequent estimation of treatment effects. The method assures that balance improves on all covariate moments included in the reweighting. It also obviates the need for continual balance checking and iterative searching over propensity score models that may stochastically balance the covariate moments. We demonstrate the use of entropy balancing with Monte Carlo simulations and empirical applications.

{code}

[exalate-issue-sync[bot]]

Nidhi Mehta commented: We need to estimate the amount of work and time that will be needed to implement this.

[hasithjp]

JIRA Issue Migration Info

Jira Issue: PUBDEV-4700 Assignee: Michal Kurka Reporter: Nidhi Mehta State: Open Fix Version: N/A Attachments: N/A Development PRs: N/A