This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 32
Type: Contributed
Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #308249
Title: A Factor-Augmented Random Effects Model to Model the Association Between Cognitive Performance and Nutrition
Author(s): Sherry Lin*+ and Robert E. Weiss
Companies: University of California, Los Angeles and University of California, Los Angeles School of Public Health
Address: , , CA, 90049,
Keywords: dynamic factor model ; continuous time ; Kalman filter smoother ; MCMC
Abstract:

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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