|  | O'Hagan, Anthony / Buck, Caitlin E. / Daneshkhah, Alireza / Eiser, Richard / Garthwaite, Paul / Jenkinson, David / Oakley, Jeremy / Rakow, Tim
Uncertain Judgements
Eliciting Experts' Probabilities
Statistics in Practice
 1. Auflage Juli 2006
63,90 Euro
2006. 338 Seiten, Hardcover
ISBN 978-0-470-02999-2 - John Wiley & Sons
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| Kurzbeschreibung
Uncertain Judgments Eliciting Experts' Probabilities presents a range of tried and tested elicitation methods to enable statisticians to get make the most of expert opinion. An elicitation method forms a bridge between an expert¿s opinion and an expression of these points in a statistically useful form. The development of an elicitation method therefore requires an understanding of both psychology and statistics. This book, written by a group of expert statisticians and psychologists provides an introduction to the subject and a detailed overview of the existing literature. The book guides the reader through the design of an elicitation method and details examples from a cross section of literature in the statistics, psychology, engineering, and health sciences disciplines.
Aus dem Inhalt
Preface.
1. Fundamentals of Probability and Judgement.
1.1 Introduction.
1.2 Probability and elicitation.
1.3 Uncertainty and the interpretation of probability.
1.4 Elicitation and the psychology of judgement.
1.5 What use are such judgements?
1.6 Conclusions.
2. The Elicitation Context.
2.1 How and who?
2.2 What is an expert?
2.3 The elicitation process.
2.4 Conventions in Chapters 3 to 9.
2.5 Conclusions.
3. The Psychology of Judgement Under Uncertainty.
3.1 Introduction.
3.2 Understanding the task and the expert.
3.3 Understanding research on human judgement.
3.4 The heuristic and biases research programme.
3.5 Experts and expertise.
3.6 Three meta theories of judgement.
3.7 Conclusions.
4. The Elicitation of Probabilities.
4.1 Introduction.
4.2 The Calibration of Subjective Probabilities.
4.3 The calibration in subjective probabilities: theories and explanations.
4.4 Representations and methods.
4.5 Debiasing.
4.6 Conclusions.
5. Eliciting Distributions - General.
5.1 From probabilities to distributions.
5.2 Eliciting univariate distributions.
5.3 Eliciting multivariate distributions.
5.4 Uncertainty and imprecision.
5.5 Conclusions.
6. Eliciting and Fitting a Parametric Distribution.
6.1 Introduction.
6.2 Outline of this chapter.
6.3 Eliciting opinion about a proportion.
6.4 Eliciting opinion about a general scalar quantity.
6.5 Eliciting opinion about a set of proportions.
6.6 Eliciting opinion about the parameters of a multivariate normal distribution.
6.7 Eliciting opinion about the parameters of a linear regression model.
6.8 Eliciting opinion about the parameters of a generalized linear model.
6.9 Elicitation methods for other problems.
6.10 Deficiencies in existing research.
6.11 Conclusions.
7. Eliciting Distributions - Uncertainty and Imprecision.
7.1 Introduction.
7.2 Imprecise probabilities.
7.3 Incomplete information.
7.4 Summary.
7.5 Conclusions.
8. Evaluating Elicitation.
8.1 Introduction.
8.2 Scoring rules.
8.3 Coherence, feedback and overfitting.
8.4 Conclusions.
9. Multiple Experts.
9.1 Introduction.
9.2 Mathematical aggregation.
9.3 Behavioural aggregation.
9.4 Discussion.
9.5 Elicitation practice.
9.6 Research questions.
10. Published Examples of the Formal Elicitation of Expert Opinion.
10.1 Some applications.
10.2 An example of an elicitation interview - eliciting engine sales.
10.3 Medicine.
10.4 The nuclear industry.
10.5 Veterinary science.
10.6 Agriculture.
10.7 Meteorology.
10.8 Business studies, economics and finance.
10.9 Other professions.
10.10 Other examples of the elicitation of subjective probabilities.
11. Guidance on Best Practice.
12. Areas for Research.
Glossary.
Bibliography.
Author Index.
Index.
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