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Multiple Data Sources, Missing and Biased Data

Presented by: 
D de Angelis University of Cambridge
Wednesday 21st August 2013 - 12:00 to 12:30
INI Seminar Room 1
Session Title: 
Experimental Design and Inference
Inferential methods based on multiple data sources are becoming increasingly common in infectious disease epidemiology, to combine heterogeneous, incomplete and biased evidence. We describe a Bayesian approach to evidence synthesis, highlight its ability to incorporate all available information in a single coherent probabilistic model and discuss current challenges in this area.
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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons