Bias in Odds Ratios From Logistic Regression Methods With Sparse Data Sets

Bias in Odds Ratios From Logistic Regression Methods With Sparse Data Sets

Background: Logistic regression models are widely used to evaluate the association between a binary outcome and a set of covariates. However, when there are few study participants at the outcome and covariate levels, the models lead to bias of the odds ratio (OR) estimated using the maximum likeliho...

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Bibliographic Details
Main Authors: Masahiko Gosho, Tomohiro Ohigashi, Kengo Nagashima, Yuri Ito, Kazushi Maruo
Format: Article
Language:English
Published: Japan Epidemiological Association 2023-06-01
Series:Journal of Epidemiology
Subjects:
bayesian methods
exact logistic regression method
firth’s penalization
ɡ-prior
Online Access:https://www.jstage.jst.go.jp/article/jea/33/6/33_JE20210089/_pdf

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https://www.jstage.jst.go.jp/article/jea/33/6/33_JE20210089/_pdf

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