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Abstract Details
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Activity Number:
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580
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 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 - #304296 |
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Title:
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An Absolute Risk Model for Population-Based Survey Data
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Author(s):
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Stephanie Kovalchik*+ and Ruth Pfeiffer
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Companies:
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National Cancer Institute and National Cancer Institute
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Address:
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11903 Parklawn Dr, North Bethesda, MD, 20852, United States
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Keywords:
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absolute risk ;
prediction ;
survey data ;
NHANES ;
mortality ;
influence
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Abstract:
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Absolute risk models can help assess the impact that certain health characteristics have on the risk of disease. National survey data are rich sources for studying how modifiable health factors influence cause-specific disease outcomes in a well-defined population. We develop methods for building an absolute risk model from survey data and apply our methods to NHANES data to predict the impact of weight, smoking status, and alcohol consumption on the absolute risk of all-cause, cancer-specific, and cardiovascular-related death. We use weighted maximum likelihood methods to estimate population-based risk projections, and we quantify the uncertainty of these predictions using an influence-based variance. The performance of the absolute risk model is evaluated with population-based measures of calibration and discrimination.
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