Bayesian Statistical Methods
Workshop Program

THURSDAY November 13, 1997, 8:00 a.m. to 5:30 p.m.

Units 1-7: Introduction to Bayesian Statistical Approaches. Donald A. Berry (Duke University).

1. Introduction to Bayesian methods; learning under uncertainty; statistics and the scientific method; comparisons between Bayesian and frequentist approaches--philosophy and methodology

2. Bayesian vs. frequentist calculations in standard problems; dichotomous sampling; prediction; examples

3. Bayesian vs. frequentist calculations for general sampling; handling multiplicities; examples.

4. Using available information; assessing prior distributions

5. Decision analysis; utilities and losses; designing experiments; examples

6. Using historical information; hierarchical modeling; Markov chain Monte Carlo and other computational methods

7. Issues in bioassay; examples

Units 8-12: Applications

8. Applications of Bayesian Methods in Radiation Protection Peter G. Groer (University of Tennessee, Knoxville) 

9. Bayesian Analysis of Internal Dosimetry Problems Tom LaBone (Westinghouse Savannah River Company)

10. Support for Bayesian Statistics Harry F. Martz (Los Alamos National Laboratory)

11. Optimal Decision Levels Mario E. Schillaci (Los Alamos National Laboratory)

11. Use of Bayesian Computational Tools to Solve Real Health Physics Problems Guthrie Miller (Los Alamos National Laboratory)

12. Panel Discussion and Consensus Development: Use of Bayesian Statistical Inference in Bioassay and Internal Dosimetry

Panel Members: Donald A. Berry (Duke University), Donald E. Bihl (Pacific Northwest National Laboratory), Allen Brodsky (Science Applications International Corporation), Peter G. Groer (University of Tennessee - Knoxville), Thomas R. La Bone (Westinghouse Savannah River Company), Guthrie Miller (Los Alamos National Laboratory), Joel. L. Rabovsky (U.S. Department of Energy, EH-52), Mario E. Schillaci (Los Alamos National Laboratory), Daniel J. Strom (Moderator; Pacific Northwest National Laboratory).