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Activity Number:
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229
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #301453 |
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Title:
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Bootstrap Variance Estimation for Predicted Individual and Population-Average Risks
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Author(s):
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Milorad Kovacevic*+ and Georgia Roberts and Lenka Mach
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Companies:
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Statistics Canada and Statistics Canada and Statistics Canada
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Address:
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15 R.H.C. Coats Building, Ottawa, ON, K1A0T6, Canada
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Keywords:
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Logistic model ; prediction models ; standard error ; validation sample ; survey bootstrap ; design-based variance
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Abstract:
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Often there is a need to predict the probability that an individual with specific characteristics (risk factors) will suffer from a certain disease or a health condition. Sometimes the real interest is in providing the aggregate predicted risk estimates at the population level or at the level of a subpopulation (e.g., males age 65+). A related problem is prediction of such a probability for an individual who does not belong to the surveyed population. While the estimation of these probabilities follows from fitting an appropriate model to the available data, the design-based standard error estimation of so-obtained estimates is not obvious. We are proposing a bootstrap method for estimation of the standard errors of predicted individual and aggregate risks. The method is illustrated using data from the Canadian Community Health Survey.
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