This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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236
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #309245 |
Title:
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Estimating a Continuously Observed Semi-Markov Process
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Author(s):
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Amy Laird*+ and Lurdes Inoue
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Companies:
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University of Washington and University of Washington
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Address:
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4514 8th Ave. NE, 1, Seattle, WA, 98105,
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Keywords:
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longitudinal study ;
chronic disease ;
semi-Markov process ;
Markov model
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Abstract:
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Longitudinal studies are a powerful method for investigating the natural history of chronic disease. Since many chronic diseases are characterized by a set of health states, a multi-state model is a natural choice. A strong yet commonly used assumption in such models, however, is that the disease process is Markovian. The semi-Markov assumption is much less restrictive, but methods for estimation and inference in semi-Markov models are still being developed. We examine some proposed parametric and nonparametric methods for estimating parameters in a semi-Markov model. We find that while the nonparametric method allows for greater modeling flexibility, it relies on a large number of observed transitions and long observation of the disease process, which may not be a realistic assumption for biomedical studies. In this talk, we will discuss the results from our simulation studies.
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Authors who are presenting talks have a * after their name.
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