A Bayesian approach for analyzing zero-inflated clustered count data with dispersion-Reference-Cited by-同舟云学术

A Bayesian approach for analyzing zero-inflated clustered count data with dispersion

Published:2017-11-06 Issue:5 Volume:37 Page:801-812
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Choo-Wosoba Hyoyoung¹^ORCID,Gaskins Jeremy²,Levy Steven³,Datta Somnath⁴^ORCID

Affiliation:

1. Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute; National Institutes of Health; 9609 Medical Center Drive Rockville Maryland 20850 USA

2. Department of Bioinformatics and Biostatistics; University of Louisville; Louisville Kentucky 40202 USA

3. Department of Preventive and Community Dentistry, Department of Epidemiology; University of Iowa; Iowa City Iowa 52242 USA

4. Department of Biostatistics; University of Florida; Gainesville Florida 32610 USA

Funder

National Institutes of Health

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

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4. A marginalized zero-inflated Poisson regression model with overall exposure effects;Long;Stat Med,2014

5. On the use of zero-inflated and hurdle models for modeling vaccine adverse event count data;Rose;J Biopharm Stat,2006

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3. Bayesian clustering of multiple zero-inflated outcomes;Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences;2023-03-27

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