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Activity Number:
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343
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Type:
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Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307318 |
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Title:
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Modeling Variability in Longitudinal Data Using Random Changepoint Models
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Author(s):
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Annica Dominicus*+ and Samuli Ripatti and Juni Palmgren+
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Companies:
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Karolinska Institutet and Karolinska Institutet and Karolinska Institutet
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Address:
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Box 281, Stockholm, 17177, Sweden Box 281, Stockholm, 17177, Sweden
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Keywords:
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change-point model ; non-linear mixed model ; first order linearization ; Gibbs sampling
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Abstract:
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Some cognitive functions exhibit multiple phases in old age, which motivates the use of a change point model for the individual trajectory from repeated measures data. The change point varies between individuals and is treated as random. We contrast the random change point model with linear and quadratic random effects models, focusing primarily on trait variability over age groups. The methods are illustrated using Swedish data on cognitive function in old age and through simulations. We show that the models impose different restrictions on the trait variance over age groups, and we demonstrate that the random change point model has favorable properties. As estimation methods we discuss the performance of approximate maximum likelihood estimation based on first order linearization of the random change point model as well as a Bayesian Gibbs sampling procedure.
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