Uncertain Judgements – Eliciting Experts′ Probabilities

Professor Anthony O'Hagan is the Director of The Centre for Bayesian Statistics in Health Economics at the University of Sheffield. The Centre is a collaboration between the Department of Probability and Statistics and the School of Health and Related Research (ScHARR). The Department of Probability and Statistics is internationally respected for its research in Bayesian statistics, while ScHARR is one of the leading UK centres for economic evaluation. Prof O'Hagan is an internationally leading expert in Bayesian Statistics. Co-authors: Professor Paul Gathwaite - Open University, Prof of Statistics, Maths and Computing Dr Jeremy Oakley - Sheffield University Professor John Brazier - Director of Health Economics Group, University of Sheffield Dr Tim Rakow - University of Essex, Psychology Department Dr Alireza Daneshkhah - University of Sheffield, Medical Statistics Department Dr Jim Chilcott - School of Health Research, University of Sheffield, Department of OR

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. 3.4.6 The affect heuristic. 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.