Bayesian Analyses Using SAS®

Biostatisticians, epidemiologists, and social scientists who are interested in the Bayesian analysis approach

• Explain the concepts of Bayesian analysis
• Illustrate Bayesian analyses in PROC GENMOD, PROC PHREG, and PROC MCMC
• Incorporate prior distributions in a Bayesian analysis
• Illustrate a Bayesian analysis approach to a meta-analysis

Before attending this course, you should:

• Be able to create SAS data sets and manipulate data. You can gain this experience from the SAS Programming 2: Data Manipulation Techniques course
• Have completed a statistics course such as the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression or Statistics 2: ANOVA and Regression course

Introduction to Bayesian Analysis

• Introduce the basic concepts of Bayesian analysis
• Compute the diagnostic plots and diagnostic statistics for model assessment
• Discuss the advantages and disadvantages of Bayesian analysis
• Illustrate a Bayesian analysis in PROC GENMOD and PROC PHREG

Fitting Models with the MCMC Procedure

• Show the essential statements in PROC MCMC
• Show the supported distributions in PROC MCMC
• Fit a logistic regression model in PROC MCMC
• Fit a general linear mixed model in PROC MCMC
• Fit a zero-inflated Poisson model in PROC MCMC
• Incorporate missing values in PROC MCMC

Bayesian Approaches to Clinical Trials

• Use prior distributions in a Bayesian analysis
• Illustrate a Bayesian approach to clinical trials using PROC MCMC
• Illustrate the Bayesian approach to meta-analysis