Bayesian Analyses Using SAS®
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Bayesian Analyses Using SAS®
Duration: 14 hours
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.
Learn How To
  • 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 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 1: Introduction to ANOVA, Regression, and Logistic Regression or Statistics 2: ANOVA and Regression course.
  • SAS Products Covered
    SAS/STAT;SAS/GRAPH
    Course Outline
    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.

  • Live Instructor Dates SOLD SEPARATELY
    DATES ▼ LOCATION
    TIME
    LANGUAGEEVENT FEE
    08-11 JUL 2025Live Web, US1:00 PM-4:30 PM EDTEnglish2,000 USD
    02-05 DEC 2025Live Web, US1:00 PM-4:30 PM ESTEnglish2,000 USD


    THIS COURSE IS PART OF

    SAS Statistics Foundations​ Learning Subscription



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