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AMBIGUITY

UNCERTAINTY. 2: Expert Judgment for Quantifying Uncertainty. AMBIGUITY. Roger Cooke Resources for the Future Dept. Math, Delft Univ. of Technology April 15,16 2008. INDECISION. UNCERTAINTY. AMBIGUITY. INDECISION. 2.

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AMBIGUITY

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  1. UNCERTAINTY 2: Expert Judgmentfor Quantifying Uncertainty AMBIGUITY Roger Cooke Resources for the Future Dept. Math, Delft Univ. of Technology April 15,16 2008 INDECISION

  2. UNCERTAINTY AMBIGUITY INDECISION 2 “Uncertainty from random sampling ...omits important sources of uncertainty” NRC(2003) All cause mortality, percent increase per 1 μg/m3 increase in PM2.5 (RESS-PM25.pdf)

  3. UNCERTAINTY AMBIGUITY Very Different Guidelines: The story you hear today is NOT the only story INDECISION 2 History Structured Expert Judgment in Risk Analysis • WASH 1400 (Rasmussen Report, 1975) • IEEE Std 500 (1977) • Canvey Island (1978) • NUREG 1150 (1989) • T-book (Swedish Reliability Data Base 1994) • USNRC-EU (1995-1997) • Guidance on Uncertainty and Use of Experts. NUREG/CR-6372, 1997 • Procedures Guide for Structured Expert Judgment, EUR 18820EN, 2000

  4. UNCERTAINTY AMBIGUITY INDECISION 2 Goals of an EJ study • Census • Political consensus • Rational consensus EJCoursenotes_review-EJ-literature.doc

  5. UNCERTAINTY AMBIGUITY INDECISION 2 EJ for RATIONAL CONSENSUS:RESS-TUDdatabase.pdf Parties pre-commit to a method which satisfies necessary conditions for scientific method: Traceability/accountability Neutrality (don’t encourage untruthfulness) Fairness (ab initio, all experts equal) Empirical control (performance meas’t) Withdrawal post hoc incurs burden of proof. Goal: comply with principals and combine experts’ judgments to get a Good Probability Assessor “Classical Model for EJ”

  6. UNCERTAINTY AMBIGUITY INDECISION 2 What is a GOOD subjective probability assessor? • Calibration, statistical likelihood • Are the expert’s probability statements statistically accurate? P-value of statistical test • Informativeness • Probability mass concentrated in a small region, relative to background measure • Nominal values near truth • ?

  7. UNCERTAINTY AMBIGUITY INDECISION 2 Combined Score • Calibration  information  cutoff Requires that experts assess uncertainty for variables for which we (will) know the true values: Calibration / performance / seed variables any expert, or combination of experts, can be regarded as a statistical hypothesis

  8. Expert elicitation techniques Delphi Nominal group techniques Group nomination Team building, decision conferencing, etc Key question: How do we measure performance Credibility via performance, period. UNCERTAINTY AMBIGUITY INDECISION 2

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