BMTRY719

BMTRY 719 : Bayesian Biostatistics

DESCRIPTION

It is a graduate course on effective and sophisticated approaches to Bayesian modeling and computation in biostatistics and related fields. The course begins with a gentle introduction of Bayesian inference starting from first principle, but it intends to cover the philosophical backgrounds, logical developments and computational tools associated with Bayesian

TOPICS:

• Bayes rule
• Bayesian inference for single parameter model
• Multiparameter models
• Connection to classical statistics
• Scopes of Bayesian statistics in medicine
• Hierarchical models in biostatistics
• Model checking and sensitivity analysis 
• Study design in Bayesian analysis
• Bayesian regression
• Computation and simulation
• Posterior simulation
• Hierarchical linear models from Bayesian perspective
• Bayesian Generalized linear model
• Multivariate models in Bayesian analysis 
• Bayesian mixture models
• Missing data in Bayesian statistics

PREREQUISITES AND OFFERINGS

BMTRY 700, 701, 706, 707.  Typically offered every other fall semester.