Robust Bayesian approach to logistic regression modeling in small sample size utilizing a weakly informative student’s t prior distribution

DOI10.1080/03610926.2021.1912767OpenAlexW3162630480MaRDI QIDQ5875221

Mohamed Kharrat, Kenneth Chukwuemeka Asanya, Emmanuel Torsen, Akaninyene Udo Udom

Publication date: 3 February 2023

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2021.1912767

zbMATH Keywords

logistic regressionoutlierweakly informative prior distributionsmall sample sizerobust Bayesian logistic

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• rjags

Cites Work

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• A weakly informative default prior distribution for logistic and other regression models
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Approximate Bayes factors and accounting for model uncertainty in generalised linear models
• Robust Estimation of a Location Parameter

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