A Proposal for Informative Default Priors Scaled by the Standard Error of Estimates

DOI10.1080/00031305.2021.1938225OpenAlexW3168004148MaRDI QIDQ5050789

Erik van Zwet, Andrew Gelman

Publication date: 18 November 2022

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.15037

zbMATH Keywords

shrinkageexaggeration ratiotype M errorWinner's curse

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• flexmix
• BayesDA

Cites Work

• Bayesian heavy-tailed models and conflict resolution: a review
• Objective priors: an introduction for frequentists
• Bayesianly justifiable and relevant frequency calculations for the applied statistician
• A weakly informative default prior distribution for logistic and other regression models
• Type S error for classical and Bayesian single and multiple comparison procedures
• Posterior expectations for large observations
• The Selection of Prior Distributions by Formal Rules
• The case for objective Bayesian analysis