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Abstract Details
Activity Number:
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229
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 1, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #302560 |
Title:
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Bayesian Semiparametric Nonstationary Correlation Models for Longitudinal Data
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Author(s):
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Robert E. Weiss*+ and Lei Qian
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Companies:
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University of California at Los Angeles and Kaiser Permanente
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Address:
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, , ,
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Keywords:
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Change point ;
CD4 Cell counts ;
Growth curve ;
B-spline ;
Covariance model
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Abstract:
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We develop a matrix mixture correlation model for continuous longitudinal data with nonstationary correlations. We consider two situations, one where there is a known change point causing nonstationarity, and a second situation where the correlations change smoothly over time. The former is appropriate when a known change in the biological system has a substantial impact on outcomes. The second situation with continuously changing correlation happens for example in growth curve studies where growth in early life is very different from later growth. Our model allows both the correlation values and underlying structure to change over time and is capable of handling highly unbalanced data with a large number of repeated measurements.
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