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Activity Number: 421
Type: Topic Contributed
Date/Time: Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract - #308732
Title: Estimating Nonhomogeneous Intensity Matrices in Continuous Time Multi-State Markov Models
Author(s): Gerald Lebovic*+ and George Tomlinson and Patrick Brown and James Stafford
Companies: St. Michael's Hospital and University Health Network and University of Toronto and University of Toronto
Keywords: Markov ; Multi-State Model ; local likelihood ; EM algorithm ; intensity
Abstract:

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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