This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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337
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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Abstract - #308078 |
Title:
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Nonidentifiability in the Context of Missing Confounders
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Author(s):
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Lawrence McCandless*+
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Companies:
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Simon Fraser University
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Address:
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Faculty of Health Sciences, Burnaby, V5A 1S6, Canada
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Keywords:
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Epidemiology ;
Bayesian statistics ;
Causal inference ;
MCMC
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Abstract:
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Non-identifiable models frequently arise in epidemiology, which is concerned with exploring the cause and effect relationships between exposure and disease. One reason is because study participants are not randomly assigned to exposure groups, which makes it difficult to distinguish association from causation. Causal effects cannot be estimated without strong and untestable assumptions about how the data were generated. In this presentation I will discuss Bayesian analysis of non-identifiable models in epidemiology with special emphasis on the problem of missing confounders. The discussion will highlight MCMC sampler convergence and choosing appropriate prior distributions.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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