The course focuses on Bayesian analyses using the PHREG, GENMOD, and MCMC procedures. The examples include logistic regression, Cox proportional hazards model, general linear mixed model, zero-inflated Poisson model, and data containing missing values. A Bayesian analysis of a crossover design and a meta-analysis are also shown.
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual lab time to practice.
- 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.
Who Can Benefit
- Biostatisticians, epidemiologists, and social scientists who are interested in the Bayesian analysis approach
- 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.