An improved estimator of the logarithmic odds ratio for small sample sizes using a Bayesian approach

Ogura Toru () and Yanagimoto Takemi
Additional contact information
Ogura Toru: Clinical Research Support Center, 220937 Mie University Hospital , 2-174, Edobashi, Tsu City, Mie, 514-8507, Japan
Yanagimoto Takemi: Institute of Statistical Mathematics, 10-3, Midorimachi, Tachikawa-City, Tokyo, 190-856, Japan

The International Journal of Biostatistics, 2025, vol. 21, issue 1, 151-163

Abstract: The logarithmic odds ratio is a well-known method for comparing binary data between two independent groups. Although various existing methods proposed for estimating a logarithmic odds ratio, most methods estimate two proportions in each group independently and then estimate the logarithmic odds ratio using the two estimated proportions. When using a logarithmic odds ratio, researchers are more interested in the logarithmic odds ratio than proportions for each group. Parameter estimations, generally, incur random and systematic errors. These errors in initially estimated parameter may affect later estimated parameter. We propose a Bayesian estimator to directly estimate a logarithmic odds ratio without using proportions for each group. Many existing methods need to estimate two parameters (two proportions in each group) to estimate a logarithmic odds ratio; however, the proposed method only estimates one parameter (logarithmic odds ratio). Therefore, the proposed estimator can be closer to the population’s logarithmic odds ratio than existing estimators. Additionally, the validity of the proposed estimator is verified using numerical calculations and applications.

Keywords: binary data; credibility test; risk comparison; 2 × 2 contingency table (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/ijb-2024-0105 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:ijbist:v:21:y:2025:i:1:p:151-163:n:1013

Ordering information: This journal article can be ordered from
https://www.degruyte ... journal/key/ijb/html

DOI: 10.1515/ijb-2024-0105

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().