Uncertain Judgements: Eliciting Expert Probabilities不确定判断:引发专家概率
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ISBN:9780470029992
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简介
Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples. 作者简介 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.
目录
Preface
1 Fundamentals of Probability and Judgement
1.1 Introduction
1.2 Probability and ehcltatlon
1.2.1 Probability
1.2.2 Random variables and probability distributions
1.2.3 Summaries of distributions
1.2.4 Joint distributions
1.2.5 Bayes' Theorem
1.2.6 Elicitation
1.3 Uncertainty and the interpretation of probability
1.3.1 Aleatory and epistemic uncertainty
1.3.2 Frequency and personal probabilities
1.3.3 An extended example
1.3.4 Implications for elicitation
1.4 Elicitation and the psychology of judgement
1.4.1 Judgement - absolute or relative?
1.4.2 Beyond perception
1.4.3 Implications for elicitation
1.5 Of what use are such judgements?
1.5.1 Normative theories of probability
1.5.2 Coherence
1.5.3 Do elicited probabilities have the desired interpretation?
1.6 Conclusions
1.6.1 Elicitation practice
1.6.2 Research questions
2 The Elicitation Context
2.1 How and who?
2.1.1 Choice of format
2.1.2 What is an expert?
2.2 The elicitation process
2.2.1 Roles within the elicitation process
2.2.2 A model for the elicitation process
2.3 Conventions in Chapters 3 to 9
2.4 Conclusions
2.4.1 Elicitation practice
2.4.2 Research question
3 The Psychology of Judgement Under Uncertainty
3.1 Introduction
3.1.1 Why psychology?
3.1.2 Chapter overview
3.2 Understanding the task and the expert
3.2.1 Cognitive capabilities: the proper view of human informa- tion processing?
3.2.2 Constructive processes: the proper view of the process?
3.3 Understanding research on human judgement
3.3.1 Experts versus the rest: the proper focus of research?
3.3.2 Early research on subjective probability: 'conservatism' in Bayesian probability revision
3.4 The heuristics and biases research programme
3.4.1 Availability
3.4.2 Representativeness
3.4.3 Do frequency representations remove the biases attributed to availability and representativeness?
3.4.4 Anchoring-and-adjusting
3.4.5 Support theory
3.4.6 The affect heuristic
3.4.7 Critique of the heuristics and biases approach
3.5 Experts and expertise
3.5.1 The heuristics and biases approach
3.5.2 The cognitive science approach
3.5.3 'The middle way'
3.6 Three meta-theories of judgement
3.6.1 The cognitive continuum
3.6.2 The inside versus the outside view
3.6.3 The naive intuitive statistician metaphor
3.7 Conclusions
3.7.1 Elicitation practice
3.7.2 Research questions
4 The Eiicitation of Probabilities
4. 1 Introduction
4.2 The calibration of subjective probabilities
4.2.1 Research methods in calibration research
……
5 Eliciting Distributions-General
6 Eliciting and Fitting a Parametric Distribution
7 Elicting Distributions-Uncertainty and Imprecision
8 Evaluating Elictation
9 Multiple Experts
10 Published Examples of the Formal Elicitation of Expert Opinion
11 Guidance on Best Practice
12 Areas for Research
Glossary
Bibliography
Author Index
Index
1 Fundamentals of Probability and Judgement
1.1 Introduction
1.2 Probability and ehcltatlon
1.2.1 Probability
1.2.2 Random variables and probability distributions
1.2.3 Summaries of distributions
1.2.4 Joint distributions
1.2.5 Bayes' Theorem
1.2.6 Elicitation
1.3 Uncertainty and the interpretation of probability
1.3.1 Aleatory and epistemic uncertainty
1.3.2 Frequency and personal probabilities
1.3.3 An extended example
1.3.4 Implications for elicitation
1.4 Elicitation and the psychology of judgement
1.4.1 Judgement - absolute or relative?
1.4.2 Beyond perception
1.4.3 Implications for elicitation
1.5 Of what use are such judgements?
1.5.1 Normative theories of probability
1.5.2 Coherence
1.5.3 Do elicited probabilities have the desired interpretation?
1.6 Conclusions
1.6.1 Elicitation practice
1.6.2 Research questions
2 The Elicitation Context
2.1 How and who?
2.1.1 Choice of format
2.1.2 What is an expert?
2.2 The elicitation process
2.2.1 Roles within the elicitation process
2.2.2 A model for the elicitation process
2.3 Conventions in Chapters 3 to 9
2.4 Conclusions
2.4.1 Elicitation practice
2.4.2 Research question
3 The Psychology of Judgement Under Uncertainty
3.1 Introduction
3.1.1 Why psychology?
3.1.2 Chapter overview
3.2 Understanding the task and the expert
3.2.1 Cognitive capabilities: the proper view of human informa- tion processing?
3.2.2 Constructive processes: the proper view of the process?
3.3 Understanding research on human judgement
3.3.1 Experts versus the rest: the proper focus of research?
3.3.2 Early research on subjective probability: 'conservatism' in Bayesian probability revision
3.4 The heuristics and biases research programme
3.4.1 Availability
3.4.2 Representativeness
3.4.3 Do frequency representations remove the biases attributed to availability and representativeness?
3.4.4 Anchoring-and-adjusting
3.4.5 Support theory
3.4.6 The affect heuristic
3.4.7 Critique of the heuristics and biases approach
3.5 Experts and expertise
3.5.1 The heuristics and biases approach
3.5.2 The cognitive science approach
3.5.3 'The middle way'
3.6 Three meta-theories of judgement
3.6.1 The cognitive continuum
3.6.2 The inside versus the outside view
3.6.3 The naive intuitive statistician metaphor
3.7 Conclusions
3.7.1 Elicitation practice
3.7.2 Research questions
4 The Eiicitation of Probabilities
4. 1 Introduction
4.2 The calibration of subjective probabilities
4.2.1 Research methods in calibration research
……
5 Eliciting Distributions-General
6 Eliciting and Fitting a Parametric Distribution
7 Elicting Distributions-Uncertainty and Imprecision
8 Evaluating Elictation
9 Multiple Experts
10 Published Examples of the Formal Elicitation of Expert Opinion
11 Guidance on Best Practice
12 Areas for Research
Glossary
Bibliography
Author Index
Index
Uncertain Judgements: Eliciting Expert Probabilities不确定判断:引发专家概率
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