Bayesian Analyses Using SAS - STBAY
The course focuses on Bayesian analyses using the PHREG, GENMOD, and MCMC procedures. Most of the examples are in the area of clinical trials.
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Duration:
2 days -  Classroom |
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
Prerequisites
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.
Course Contents
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
Software Addressed
This course addresses the following software product(s): SAS/STAT, SAS/GRAPH. This course is offered on the Windows platform only using SAS 9.2.
