This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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536
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Type:
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Contributed
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Date/Time:
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Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #308546 |
Title:
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Multilevel Modeling of Follow-Up Studies with Missing Data
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Author(s):
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Monica Michelle Bennett*+ and John Seaman and James Stamey
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Companies:
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Baylor University and Baylor University and Baylor University
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Address:
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1825 S. 5th St #64, Waco, TX, 76706,
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Keywords:
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Missing data ;
Multilevel regression ;
Bayesian inference
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Abstract:
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Follow-up studies are often used to assess the rates of incidence of a particular event, such as death or injury, among different groups. The observed counts are usually assumed to follow a Poisson distribution. The analysis is complicated when some of the records indicating the cause of the incident have been destroyed or lost. If we ignore the missing data then both the overall event rates and the uncertainty in the model parameters will be underestimated. To help overcome this problem, we develop a Bayesian multilevel Poisson model to account for the missing data. The model is developed so that it estimates the rates of incidence, as well as the probability of missing information.
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