An all day short course will be held on Sunday, June 17. It will be in Lory Student Center on the Colorado State University campus.
“Fundamentals of Bayesian Analysis with Examples”
Presentor: Mike Patetta , SAS Institute Inc.
I. Introduction to Bayesian Analysis
a. Introduce the basic concepts of Bayesian analysis.
b. Illustrate the differences between Bayesian analysis and classical statistics.
c. Illustrate the Metropolis sampling algorithm.
d. Introduce the Markov chain diagnostic statistics.
e. Explain the advantages and disadvantages of Bayesian analysis.
II. Bayesian Model Fitting
a. Model specification essentials: parameters, prior distributions and likelihood.
b. Fit a Bayesian logistic regression model.
c. Fit a Bayesian general linear mixed model.
d. Fit a zero-inflated Poisson model.
III. Bayesian Approaches to Clinical Trials
a. Discuss different ways to construct informative prior distributions.
b. Analyze a crossover design incorporating historical data.
c. Illustrate the advantages of meta-analysis.
d. Fit a Bayesian model on pooled data sources.
All examples will be shown using SAS software.
