Ebook: Case Studies in Bayesian Statistics

The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma­ jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth­ ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at the Workshop. In addition there are nine contributed papers, selected from the thirty-four presented at the Workshop, on a variety of applications. This collection of case studies illustrates the ways in which Bayesian methods are being incorporated into statistical practice. The strengths (and limitations) of the approach become apparent through the examples.

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The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible. The purpose of this volume is to present several detailed examples of applications of Bayesian methods. The emphasis of each article is on the scientific or technological context of the problem being solved, and much background material is provided to complete the description of the analysis. This collection illustrates the ways in which Bayesian methods are permeating statistical practice. Noteworthy in the articles are the construction of explicit and conceptually simple models, the use of information other than the data under analysis, and the representation of uncertainty from various sources in the model. Consequently, many researchers will find this collection an illuminating survey of Bayesian methods in practice, and both lecturers and students will be able to learn a great deal through study of these examples.

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The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible. The purpose of this volume is to present several detailed examples of applications of Bayesian methods. The emphasis of each article is on the scientific or technological context of the problem being solved, and much background material is provided to complete the description of the analysis. This collection illustrates the ways in which Bayesian methods are permeating statistical practice. Noteworthy in the articles are the construction of explicit and conceptually simple models, the use of information other than the data under analysis, and the representation of uncertainty from various sources in the model. Consequently, many researchers will find this collection an illuminating survey of Bayesian methods in practice, and both lecturers and students will be able to learn a great deal through study of these examples.
Content:
Front Matter....Pages i-xi
Front Matter....Pages xiii-xiii
Bayesian Estimation of Fuel Economy Potential Due to Technology Improvements....Pages 1-77
Bayes Analysis of Model-Based Methods for Nonignorable Nonresponse in the Harvard Medical Practice Survey....Pages 78-117
Use of Prior Information to Estimate Costs in a Sewerage Operation....Pages 118-162
Estimation of Bowhead Whale, Balaena mysticetus, Population Size....Pages 163-240
Bayesian Decision Support Using Environmental Transport-And-Fate Models....Pages 241-293
Front Matter....Pages 295-295
Invited Discussion....Pages 297-301
Contributed Discussions....Pages 302-307
Front Matter....Pages 309-309
Bayesian Analysis of the Ames Salmonella/Microsome Assay....Pages 311-323
A Clinical Experiment in Bone Marrow Transplantation: Estimating a Percentage Point of a Quantal Response Curve....Pages 324-336
The Composition of a Composition: Just the Facts....Pages 337-350
Predicting Coproduct Yields in Microchip Fabrication....Pages 351-361
Synchronicity of Whale Strandings with Phases of the Moon....Pages 362-376
Bayesian Predictive Inference for Small Areas for Binary Variables in the National Health Interview Survey....Pages 377-389
A Cost-Utility Analysis of Alternative Strategies in Screening for Breast Cancer....Pages 390-402
Restoration and Segmentation of Rail Surface Images....Pages 403-415
Assessing Mechanisms of Neural Synaptic Activity....Pages 416-428
Back Matter....Pages 429-439

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The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible. The purpose of this volume is to present several detailed examples of applications of Bayesian methods. The emphasis of each article is on the scientific or technological context of the problem being solved, and much background material is provided to complete the description of the analysis. This collection illustrates the ways in which Bayesian methods are permeating statistical practice. Noteworthy in the articles are the construction of explicit and conceptually simple models, the use of information other than the data under analysis, and the representation of uncertainty from various sources in the model. Consequently, many researchers will find this collection an illuminating survey of Bayesian methods in practice, and both lecturers and students will be able to learn a great deal through study of these examples.
Content:
Front Matter....Pages i-xi
Front Matter....Pages xiii-xiii
Bayesian Estimation of Fuel Economy Potential Due to Technology Improvements....Pages 1-77
Bayes Analysis of Model-Based Methods for Nonignorable Nonresponse in the Harvard Medical Practice Survey....Pages 78-117
Use of Prior Information to Estimate Costs in a Sewerage Operation....Pages 118-162
Estimation of Bowhead Whale, Balaena mysticetus, Population Size....Pages 163-240
Bayesian Decision Support Using Environmental Transport-And-Fate Models....Pages 241-293
Front Matter....Pages 295-295
Invited Discussion....Pages 297-301
Contributed Discussions....Pages 302-307
Front Matter....Pages 309-309
Bayesian Analysis of the Ames Salmonella/Microsome Assay....Pages 311-323
A Clinical Experiment in Bone Marrow Transplantation: Estimating a Percentage Point of a Quantal Response Curve....Pages 324-336
The Composition of a Composition: Just the Facts....Pages 337-350
Predicting Coproduct Yields in Microchip Fabrication....Pages 351-361
Synchronicity of Whale Strandings with Phases of the Moon....Pages 362-376
Bayesian Predictive Inference for Small Areas for Binary Variables in the National Health Interview Survey....Pages 377-389
A Cost-Utility Analysis of Alternative Strategies in Screening for Breast Cancer....Pages 390-402
Restoration and Segmentation of Rail Surface Images....Pages 403-415
Assessing Mechanisms of Neural Synaptic Activity....Pages 416-428
Back Matter....Pages 429-439
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