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SUMMARY:Some Challenges with Input Uncertainty - Chick\, S (INSEAD)
DTSTART:20110908T090000Z
DTEND:20110908T093000Z
UID:TALK32718@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:In this short presentation\, I will summarize several recent a
 pplications from various parts of health care that highlight several inter
 esting challenges with modeling and input uncertainty. Beyond the usual ch
 allenges associated with Bayesian model average-type approaches for parame
 ter uncertainty about statistical input parameters\, some challenges will 
 also be identified. They include the difficulty that some decision makers 
 have in thinking about data for input parameters when output data is easie
 r to observe\, data on intermediate or surrogate endpoints may be easier o
 r less expensive to collect\, and the structure of the model that translat
 es inputs to outputs itself might be uncertain. These examples and challen
 ges have a number of implications\, many not yet adequately solved\, for p
 olicy decisions\, the sensitivity of decisions to input uncertainty\, the 
 prioritization of data to reduce input uncertainty in a way that effective
 ly\, when to stop learnin g and when to make a system design decision\, an
 d how to model extreme events (e.g.\, heavy tails) that may have implicati
 ons for the nonexistence of certain moments of interest. We will review a 
 number of these as time permits.\n
LOCATION:Seminar Room 1\, Newton Institute
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