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Activity Number:
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600
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #303449 |
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Title:
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A Two-Stage Estimation Method for Random Coefficient Differential Equation Models with Application to Longitudinal HIV Dynamic Data
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Author(s):
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Yun Fang*+ and Hulin Wu and Li-Xing Zhu
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Companies:
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East China Normal University and University of Rochester and Hong Kong Baptist University
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Address:
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No. 500, Dongchuan Rd, Minhang District, Shanghai, 200241, China
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Keywords:
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AIDS/HIV data ; Local polynomial kernel smoothing ; Longitudinal data ; Mixed-effects models ; Ordinary differential equation ; Pseudo likelihood
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Abstract:
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We propose a two-stage estimation method for random coefficient ordinary differential equation (ODE) models. A maximum pseudo-likelihood estimator (MPLE) is derived based on mixed-effects model approach and its asymptotic properties for population parameters are established. The proposed method does not require repeatedly solving ODEs and is computationally efficient although it has to pay a price to lose some estimation efficiency. It is an alternative approach when the exact likelihood approach fails due to model complexity and high-dimensional parameter space, and it can also serve as a method to obtain the starting estimates for more accurate estimation methods. The finite sample properties of the proposed estimator are studied via Monte Carlo simulations and the methodology is also illustrated with application to an AIDS clinical data set.
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