Case Studies in Bayesian Statistics

1. Front Matter

   Pages i-xiv

   PDF

2. Invited Papers

   1. Front Matter

      Pages 1-1

      PDF

   2. School Choice in NY City: A Bayesian Analysis of an Imperfect Randomized Experiment

      • John Barnard, Constantine Frangakis, Jennifer Hill, Donald B. Rubin

      Pages 3-97

   3. Adaptive Bayesian Designs for Dose-Ranging Drug Trials

      • Donald A. Berry, Peter Müller, Andy P. Grieve, Michael Smith, Tom Parke, Richard Blazek et al.

      Pages 99-181

   4. Modeling the Impact of Traffic-Related Air Pollution on Childhood Respiratory Illness

      • Nicola G. Best, Katja Ickstadt, Robert L. Wolpert, Samantha Cockings, Paul Elliott, James Bennett et al.

      Pages 183-259

3. Contributed Papers

   1. Front Matter

      Pages 261-261

      PDF

   2. A Hierarchical Model for Estimating Distribution Profiles of Soil Texture

      • Pamela J. Abbitt, F. Jay Breidt

      Pages 263-278

   3. Assessing the Homogeneity of Three Odds Ratios: A Case Study in Small-Sample Inference

      • John B. Carlin

      Pages 279-290

   4. Modeling Rates of Bone Growth and Loss Using Order-Restricted Inference and Stochastic Change Points

      • Richard B. Evans, J. Sedransk, Siu L. Hui

      Pages 291-307

   5. Estimating Genotype Probabilities in Complex Pedigrees

      • Soledad A. Fernández, Rohan L. Fernando, Alicia L. Carriquiry, Bernt Guldbrandtsen

      Pages 309-328

   6. Identifying Carriers of a Genetic Modifier Using Nonparametric Bayesian Methods

      • Peter D. Hoff, Richard B. Halberg, Alexandra Shedlovsky, William F. Dove, Michael A. Newton

      Pages 329-343

   7. Bayesian Tools for EDA and Model Building: A Brainy Study

      • Steven N. MacEachern, Mario Peruggia

      Pages 345-362

   8. Bayesian Protein Structure Prediction

      • Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag

      Pages 363-378

   9. Bayesian Analysis of Sensory Inputs of a Mobile Robot

      • Paola Sebastiani, Marco Ramoni, Paul Cohen

      Pages 379-395

   10. Hidden Markov Models for Analysis of Biological Rhythm Data

       • Howard J. Seltman

       Pages 397-405

   11. Using Prior Opinions to Examine Sample Size in Two Clinical Trials

       • Chin-Pei Tsai, Kathryn Chaloner

       Pages 407-421

4. Back Matter

   Pages 423-438

   PDF

The 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24-25, 1999. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the three invited case studies with the accompanying discussion as well as ten contributed pa­ pers selected by a refereeing process. The majority of case studies in the volume come from biomedical research. However, the reader will also find studies in education and public policy, environmental pollution, agricul­ ture, and robotics. INVITED PAPERS The three invited cases studies at the workshop discuss problems in ed­ ucational policy, clinical trials design, and environmental epidemiology, respectively. 1. In School Choice in NY City: A Bayesian Analysis ofan Imperfect Randomized Experiment J. Barnard, C. Frangakis, J. Hill, and D. Rubin report on the analysis of the data from a randomized study conducted to evaluate the New YorkSchool Choice Scholarship Pro­ gram. The focus ofthe paper is on Bayesian methods for addressing the analytic challenges posed by extensive non-compliance among study participants and substantial levels of missing data. 2. In Adaptive Bayesian Designs for Dose-Ranging Drug Trials D. Berry, P. Mueller, A. Grieve, M. Smith, T. Parke, R. Blazek, N.

• Markov model
• Odds
• bayesian statistics
• hidden Markov model
• modeling
• randomized experiment
• statistics

• Center for Statistical Sciences, Brown University, Providence, USA

  Constantine Gatsonis

• Department of Statistics, Carnegie Mellon University, Pittsburgh, USA

  Robert E. Kass, Isabella Verdinelli

• Division of Biostatistics, University of Minnesota, Minneapolis, USA

  Bradley Carlin

• Department of Statistics, Iowa State University, Ames, USA

  Alicia Carriquiry

• Department of Statistics, Columbia University, New York, USA

  Andrew Gelman

• Institute of Statistics and Decision Sciences, Duke University, Durham, USA

  Mike West

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