Parameter Expanded Algorithms for Bayesian Latent Variable Modeling of Genetic Pleiotropy Data
نویسندگان
چکیده
منابع مشابه
Parameter Expanded Algorithms for Bayesian Latent Variable Modeling of Genetic Pleiotropy Data.
Motivated by genetic association studies of pleiotropy, we propose a Bayesian latent variable approach to jointly study multiple outcomes. The models studied here can incorporate both continuous and binary responses, and can account for serial and cluster correlations. We consider Bayesian estimation for the model parameters, and we develop a novel MCMC algorithm that builds upon hierarchical c...
متن کاملParameter Expanded Algorithms for Bayesian Latent Variable Modelling of Genetic Pleiotropy Data
Motivated by genetic association studies of pleiotropy, we propose a Bayesian latent variable approach to jointly study multiple outcomes. The models studied here can incorporate both continuous and binary responses, and can account for serial and cluster correlations. We consider Bayesian estimation for the model parameters, and we develop a novel MCMC algorithm that builds upon hierarchical c...
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2016
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2014.988337