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SUMMARY:Multiple Data Sources\, Missing and Biased Data - de Angelis\, D (
 University of Cambridge)
DTSTART:20130821T110000Z
DTEND:20130821T113000Z
UID:TALK46756@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Inferential methods based on multiple data sources are becomin
 g increasingly common in infectious disease epidemiology\, to combine   he
 terogeneous\, incomplete and biased evidence. We describe a Bayesian appro
 ach to evidence synthesis\, highlight  its ability to incorporate all avai
 lable information in a single coherent probabilistic model and discuss  cu
 rrent challenges in this area.\n
LOCATION:Seminar Room 1\, Newton Institute
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