This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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418
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #307202 |
Title:
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Two-Phase Study: Application to Gene-Environmental Interaction
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Author(s):
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Jaeil Ahn*+ and Bhramar Mukherjee
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Companies:
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University of Michigan and University of Michigan
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Address:
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Department of Biostatistics, Ann Arbor, MI, 48109,
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Keywords:
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gene-environment interaction ;
two-phase ;
case-control ;
Bayesian ;
semi-parametric ;
multivariate categorical
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Abstract:
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We address the problem of exploring gene-gene and gene-environment interaction under two-phase sampling designs. Two-phase sampling designs are often more efficient than standard case-control sampling design. The Phase I sample of a two-phase study contains inexpensive covariates on every subject included in the study base, whereas Phase II sample is a stratified sample based on the case-control status and some of the available covariates. Expensive covariates are measured only in the phase II sample. The likelihood under this study design is similar to a missing data likelihood. We consider the special case when the Phase I sample has environmental covariates and Phase II samples contain genotype data. We then build a semi-parametric Bayesian model that data adaptively incorporates gene-gene and gene-environment independence assumption, if tenable, and offers an integrated computational
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