This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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378
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Type:
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Invited
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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International Indian Statistical Association
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Abstract - #306326 |
Title:
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A Bayesian Approach to Estimating Transmission Parameters and Intervention Efficacies with Missing Data
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Author(s):
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M. Elizabeth Halloran*+ and Yang Yang and Michael J. Daniels and Ira M. Longini
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Companies:
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Fred Hutchinson Cancer Research Center/University of Washington and Fred Hutchinson Cancer Research Center and University of Florida and Fred Hutchinson Cancer Research Center/University of Washington
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Address:
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, Seattle, WA, ,
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Keywords:
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Abstract:
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During seasonal influenza epidemics, other pathogens co-circulate with influenza and cause influenza-like illness. Often only a proportion of the influenza-like illnesses are tested to confirm which pathogen is responsible. Thus, a large proportion of the specific outcomes are missing. Missing data is a general common problem in analysis of transmission studies in infectious diseases, because the infections times and time of onset and clearance of infectiousness are generally not observed. We propose a Bayesian competing-risk model for multiple co-circulating pathogens using a latent variable approach. We discuss the problem of model selection for the complex missing data problem. A simulation study demonstrates use of the approach to evaluate vaccine efficacy. We analyze a recent study of a non-pharmaceutical intervention against influenza in elementary schools.
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