The course focuses on Bayesian analyses using the PHREG, GENMOD, and MCMC procedures. Most of the examples are in the area of clinical trials.

Learn how to

• explain the concepts of Bayesian analysis
• illustrate Bayesian analyses in PROC PHREG and PROC GENMOD
• incorporate prior distributions in a Bayesian analysis
• illustrate a Bayesian analysis approach in a clinical trials setting using PROC MCMC.

Who should attend

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

Duration:  2 days

To Register

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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 I: Introduction to ANOVA, Regression, and Logistic Regression or the Statistics II: ANOVA and Regression courses.

This course addresses SAS/GRAPH, SAS/STAT software. This course is offered on the Windows platform only using SAS 9.2.

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 PHREG and PROC GENMOD

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

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
• explain the usefulness of the hierarchical model