Semiparametric Bayesian joint modeling of clustered binary and continuous outcomes with informative cluster size in developmental toxicity assessment
Author:
Affiliation:
1. Department of Applied Statistics; Chung-Ang University; Seoul South Korea
2. Division of Biostatistics; College of Public Health, The Ohio State University; Columbus Ohio
Funder
National Research Foundation of Korea
Chung-Ang University
Publisher
Wiley
Subject
Ecological Modelling,Statistics and Probability
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/env.2526/fullpdf
Reference43 articles.
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3. Explaining the Gibbs sampler;Casella;The American Statistician 46,1992
4. Bivariate latent variable models for clustered discrete and continuous outcomes;Catalano;Journal of the American Statistical Association,1992
5. A malformation incidence dose-response model incorporating fetal weight and/or litter size as covariates;Chen;Risk Analysis,1993
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1. A hierarchical constrained density regression model for predicting cluster‐level dose‐response;Environmetrics;2024-08-26
2. A Bayesian joint model for continuous and zero-inflated count data in developmental toxicity studies;Communications for Statistical Applications and Methods;2022-03-31
3. Joint analysis of binary and continuous data using skewed logit model in developmental toxicity studies;KOREAN J APPL STAT;2020
4. Marginal analysis of multiple outcomes with informative cluster size;Biometrics;2020-03-05
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