05629nam 2200757Ia 450 991102009670332120230828200748.09786610648870978128064887812806488729780470033319047003331297804700333020470033304(CKB)1000000000357088(EBL)274315(SSID)ssj0000263901(PQKBManifestationID)11256304(PQKBTitleCode)TC0000263901(PQKBWorkID)10283142(PQKB)10932683(MiAaPQ)EBC274315(OCoLC)85785187(Perlego)2787947(EXLCZ)99100000000035708820060919d2006 uy 0engur|n|---|||||txtccrUncertain judgements eliciting experts' probabilities /Anthony O'Hagan ... [et al.]London ;Hoboken, NJ Wileyc20061 online resource (339 p.)Statistics in practiceDescription based upon print version of record.9780470029992 0470029994 Includes bibliographical references (p. 267-306) and indexes.Uncertain Judgements; Contents; Preface; 1 Fundamentals of Probability and Judgement; 1.1 Introduction; 1.2 Probability and elicitation; 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 judgement1.4.1 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 Conclusions2.4.1 Elicitation practice2.4.2 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 information 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 revision3.4 The heuristics and biases research programme3.4.1 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 view3.6.3 The naive intuitive statistician metaphor3.7 Conclusions; 3.7.1 Elicitation practice; 3.7.2 Research questions; 4 The Elicitation of Probabilities; 4.1 Introduction; 4.2 The calibration of subjective probabilities; 4.2.1 Research methods in calibration research; 4.2.2 Calibration research: general findings; 4.2.3 Calibration research in applied settings; 4.2.4 A case study in probability judgement: calibration research in medicine; 4.3 The calibration of subjective probabilities: theories and explanations; 4.3.1 Explanations of probability judgement in calibration tasks4.3.2 Theories of the calibration of subjective probabilitiesElicitation 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 wideStatistics in practice.ProbabilitiesStatisticsDistribution (Probability theory)Mathematical statisticsBayesian statistical decision theoryProbabilities.Statistics.Distribution (Probability theory)Mathematical statistics.Bayesian statistical decision theory.519.54O'Hagan Anthony28422MiAaPQMiAaPQMiAaPQBOOK9911020096703321Uncertain judgements4418097UNINA