This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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32
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 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 - #308249 |
Title:
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A Factor-Augmented Random Effects Model to Model the Association Between Cognitive Performance and Nutrition
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Author(s):
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Sherry Lin*+ and Robert E. Weiss
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Companies:
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University of California, Los Angeles and University of California, Los Angeles School of Public Health
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Address:
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, , CA, 90049,
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Keywords:
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dynamic factor model ;
continuous time ;
Kalman filter smoother ;
MCMC
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Abstract:
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In nutrition studies, both predictors and outcomes are collected longitudinally and there are a large number of predictors for the outcome. We seek to model the correlation between the predictors and outcomes using a smaller number of time varying latent factors. We present a two-part longitudinal model, where latent factors are estimated using a dynamic factor model in the first part, and are incorporated into a random effects model for the cognitive outcome in the second part. The model is applied to data from a Kenya study to analyze the cognitive performance of children under different nutritional snack regimens.
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