Nonparametric Bayes modeling for case control studies with many predictors

Author:

Zhou Jing1,Herring Amy H.12,Bhattacharya Anirban3,Olshan Andrew F.24,Dunson David B.5,

Affiliation:

1. Department of Biostatistics; The University of North Carolina at Chapel Hill; Chapel Hill, North Carolina 27599 U.S.A.

2. Carolina Population Center; The University of North Carolina at Chapel Hill; Chapel Hill, North Carolina 27599 U.S.A.

3. Department of Statistics; Texas A&M University; College Station, Texas 77843 U.S.A.

4. Department of Epidemiology; The University of North Carolina at Chapel Hill; Chapel Hill, North Carolina 27599 U.S.A.

5. Departments of Statistical Science, Electrical and Computer Engineering, and Mathematics; Duke University; Durham, North Carolina 27708 U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Reference35 articles.

1. Use of selective serotonin-reuptake inhibitors in pregnancy and the risk of birth defects;Alwan;New England Journal of Medicine,2007

2. Separate sample logistic discrimination;Anderson;Biometrika,1972

3. Simple Bayesian analyses for case-control studies in cancer epidemiology;Ashby;The Statistician,1993

4. Controlling the false discovery rate: A practical and powerful approach to multiple testing;Benjamini;Journal of the Royal Statistical Society. Series B (Methodological),1995

5. Sparse Bayesian infinite factor models;Bhattacharya;Biometrika,2011

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1. Modeling association in microbial communities with clique loglinear models;The Annals of Applied Statistics;2019-06-01

2. Bayesian inference on group differences in multivariate categorical data;Computational Statistics & Data Analysis;2018-10

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