Abstract Details
Activity Number:
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421
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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SSC
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Abstract - #308732 |
Title:
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Estimating Nonhomogeneous Intensity Matrices in Continuous Time Multi-State Markov Models
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Author(s):
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Gerald Lebovic*+ and George Tomlinson and Patrick Brown and James Stafford
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Companies:
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St. Michael's Hospital and University Health Network and University of Toronto and University of Toronto
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Keywords:
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Markov ;
Multi-State Model ;
local likelihood ;
EM algorithm ;
intensity
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Abstract:
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Multi-State-Markov (MSM) models can be used to characterize the behaviour of categorical outcomes measured repeatedly over time. Kalbfleisch & Lawless (1985) and Gentleman et al. (1994) examine the MSM model under the assumption of time-homogeneous transition intensities. When intensities vary over time, current methods are less than ideal. We propose a local likelihood method (Tibshirani & Hastie, 1987; Loader, 1996) to estimate the transition intensities as continuous functions of time. We will discuss methods for obtaining confidence intervals as well as bandwidth selection. A simulation will be used to compare this new method with existing constant and piecewise constant methods for estimating intensities. A lung transplant dataset will be used to illustrate the method.
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Authors who are presenting talks have a * after their name.
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