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Activity Number:
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9
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Type:
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Invited
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Date/Time:
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Sunday, August 2, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Consulting
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| Abstract - #303025 |
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Title:
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Doubly Robust Ecological Inference
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Author(s):
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Daniel Rubin*+ and Mark J. van der Laan
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Companies:
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University of California, Berkeley and University of California, Berkeley
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Address:
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, Berkeley, CA, 94720,
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Keywords:
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double robustness ; ecological inference ; ecological regression ; ecological fallacy ; coarsening at random
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Abstract:
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The ecological inference problem is a famous longstanding puzzle that arises in many disciplines. The usual formulation in epidemiology is that we would like to quantify an exposure-disease association by obtaining disease rates among the exposed and unexposed, but only have access to exposure rates and disease rates for geographic regions. The problem is generally intractable, but can be attacked under the assumptions of King's (1997) extended technique if we can correctly specify a model for a certain conditional distribution. We introduce a procedure that is a valid approach if either the original model is correct or if we can pose a correct model for a different conditional distribution. The new method is illustrated on data concerning risk factors for diabetes.
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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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