How well can fine balance work for covariate balancing

Ruoqi Yu

Biometrics, 2023, vol. 79, issue 3, 2346-2356

Abstract: Fine balance is a matching technique to improve covariate balance in observational studies. It constrains a match to have identical distributions for some covariates without restricting who is matched to whom. However, despite its wide application and excellent performance in practice, there is very little theory indicating when the method is likely to succeed or fail and to what extent it can remove covariate imbalance. In order to answer these questions, this paper studies the limits of what is possible for covariate balancing using fine balance and near‐fine balance. The investigations suggest that given the distributions of the treated and control groups, in large samples, the maximum achievable balance by using fine balance only depends on the matching ratio (ie, the ratio of the sample size of the control group to that of the treated group). In addition, the results indicate how to estimate this matching ratio threshold without knowledge of the true distributions in finite samples. The findings are also illustrated by numerical studies in this paper.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/biom.13771

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:79:y:2023:i:3:p:2346-2356

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X

Access Statistics for this article

More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().