Abstract #300515

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JSM 2003 Abstract #300515
Activity Number: 133
Type: Contributed
Date/Time: Monday, August 4, 2003 : 12:00 PM to 1:50 PM
Sponsor: Biometrics Section
Abstract - #300515
Title: Estimating Variance and Confidence Interval for Disease Prevalence Based on Data
Author(s): Limin Clegg*+ and Mitchell H. Gail and Eric Jeffrey Feuer
Companies: National Cancer Institute and National Cancer Institute and National Institutes of Health
Address: Executive Plaza North, Room 343J, Bethesda, MD, 20892-0001,
Keywords:
Abstract:

We propose a new "Poisson" method to estimate the variance for prevalence estimates obtained by the counting method described by Gail et al.(1999) and to construct a confidence interval for the prevalence. We evaluate both the Poisson procedure and the procedure based on the bootstrap proposed by Gail et al. in simulated samples generated by resampling real data. These studies show that both variance estimators usually perform well and yield coverages of confidence intervals at nominal levels. When the number of disease survivors is very small, however, confidence intervals based on Poisson method have supranominal coverage, whereas those based on the procedure of Gail et al. tend to have below nominal coverage. For these reasons we recommend the Poisson method, which also reduces the computational burden considerably.

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