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Abstract Details
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Activity Number:
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243
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #305712 |
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Title:
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Posterior Predictive Model Assessment for Incomplete Longitudinal Data
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Author(s):
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Arkendu Chatterjee*+ and Michael Daniels
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Companies:
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University of Florida and University of Florida
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Address:
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4100 SW 20th Avenue, Gainesville, FL, 32607, United States
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Keywords:
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Posterior Predictive Distribution
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Abstract:
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We examine the operating characteristics of two approaches to assess model fit for incomplete longitudinal data. The first approach assesses fit based on replicated complete data as advocated in Gelman et al. (2005, Biometrics). The second approach assesses fit based on replicated observed data. Pros and cons of each approach are discussed and simulations and analytical results are presented that compare the power under each approach.
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