Multivariate Bayesian logistic regression for analysis of clinical study safety issues

DOI10.1214/11-STS381zbMath1331.62416arXiv1210.0385MaRDI QIDQ252770

William H. DuMouchel

Publication date: 4 March 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1210.0385

zbMATH Keywords

sparse dataadverse drug reactionsBayesian shrinkagedata granularitydrug safetyhierarchical Bayesian modelparallel logistic regressionsvariance component estimation

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) General nonlinear regression (62J02)

Related Items (4)

Multivariate hierarchical Bayesian models and choice of priors in the analysis of survey data ⋮ Hierarchical models for multiple, rare outcomes using massive observational healthcare databases ⋮ Bayesian Approach for Clinical Trial Safety Data Using an Ising Prior ⋮ An answer to multiple problems with analysis of data on harms?

Cites Work

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• Decoding the h-likelihood
• A weakly informative default prior distribution for logistic and other regression models
• Accounting for Multiplicities in Assessing Drug Safety: A Three-Level Hierarchical Mixture Model
• Generalized Linear Models with Random Effects

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