Refinements on the exact method to solve the numerical difficulties in fitting the log binomial regression model for estimating relative risk-Reference-Cited by-同舟云学术

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Refinements on the exact method to solve the numerical difficulties in fitting the log binomial regression model for estimating relative risk

Published:2023-11-24 Issue: Volume: Page:1-17
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Zhu Chao¹²,Hosmer David W.³,Stankovich Jim¹,Wills Karen²,Blizzard Leigh²

Affiliation:

1. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia

2. Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia

3. Department of Mathematics and Statistics, University of Vermont, Burlington, Vermont, USA

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2023.2284674

Reference18 articles.

1. Parameter Estimation and Goodness-of-Fit in Log Binomial Regression

2. Quasi-likelihood estimation for relative risk regression models

3. On the estimation of relative risks via log binomial regression;de Andrade B. B.;Revista Brasileira de Biometria,2011

4. Some results for maximum likelihood estimation of adjusted relative risks

5. Deddens, J. A., M. R. Petersen, and X. Lei. 2003. Estimation of prevalence ratios when PROC GENMOD does not converge. In Proceedings of the 28th Annual SAS Users Group International Conference, 270–28.

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