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Activity Number:
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440
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #304190 |
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Title:
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Interval Estimators for Directly Standardized Rates
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Author(s):
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Tracy Pondo*+ and Charles E. Rose and Amanda C. Cohn and Elizabeth R. Zell
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Companies:
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CDC and CDC and CDC and CDC
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Address:
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1600 Clifton Road, Atlanta, GA, 30333,
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Keywords:
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Bayesian ; Credible Intervals ; Standardized Rates
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Abstract:
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The Active Bacterial Core surveillance (ABCs) system is an active laboratory and population based surveillance system for invasive bacterial pathogens with a ten state catchment area. Disease rates in the ABCs surveillance population are directly standardized to the US population by age and race categories to estimate national disease rates. We will evaluate four interval estimators for directly standardized rates of meningococcal disease that occurred in the US from 1998--2007. Three commonly used interval estimators will be compared to Bayesian credible intervals calculated as a function of the Poisson distributed observed case counts. The Bayesian method will be compared to traditional confidence limits for directly standardized rates based on the normal distribution, interval estimators proposed by Dobson et al., and interval estimators developed by Fay and Feuer.
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