To provide researchers with an introduction to practical Bayesian methods. Topics will include Bayesian philosophy, simple and more complex models, linear and logistic regression, hierarchical models, diagnostic tests, sample size methods, issues in clinical trials, measurement error and missing data problems. Numerical techniques including Monte Carlo integration, sampling importance resampling (SIR), and the Gibbs sampler will be covered, including programming in R and WinBUGS. While all examples will be to epidemiological research, most of the ideas and material will be applicable to other areas of research.

Mondays and Wednesdays 11 AM - 12:30 PM (Jan 9 - April 16).

Mondays: Purvis Hall Room 24
Wednesdays: Purvis Hall Room 24 except for January 25, February 15, February 29, March 7, March 19, March 21, April 4, April 11, Room 25.

Ten asignments, worth 10% each. There will be no midterm or final exams.

Assignment 1: due January 25, 2012
Assignment 2: due February 1, 2012
Assignment 3: due February 8, 2012
Assignment 4: due February 27, 2012
Assignment 5: due March 5, 2012
Assignment 6: due March 12, 2012
Assignment 7: due March 21, 2012
Assignment 8: due April 2 2012
Assignment 9: due April 11, 2012
Assignment 10: due April 16, 2012

Andrew Gelman, John Carlin, Hal Stern and Donald Rubin. Bayesian Data Analysis, 2nd Edition, Chapman and Hall, 2003.
Textbook review of Gelman et al

EPIB-607 and EPIB-621, or equivalent.