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A generalized Agresti-Coull type confidence interval for a binomial proportion

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Issue Date
Publisher
한국통계학회
Citation
Journal of the Korean Statistical Society
Abstract
One of the fundamental topics in statistical inference is constructing a confidence interval for a binomial proportion p. It is well known that commonly used asymptotic confidence intervals, such as the Wilson and Agresti-Coull confidence intervals, suffer from systematic bias and oscillations in their coverage probabilities. We generalize asymptotic confidence intervals, including the Wald, Wilson and Agresti-Coull intervals, and propose a generalized Agresti-Coull type confidence interval by adjusting the bias with the saddlepoint approximation. We compare the coverage probabilities and lengths of the proposed confidence interval with those of other popular asymptotic confidence intervals. We show that the proposed confidence interval is more stable than the Wilson interval at the boundaries of p and has a shorter length than the Agresti-Coull interval.
ISSN
1226-3192
URI
https://hdl.handle.net/10371/179512
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College of Natural Sciences (자연과학대학)Dept. of Statistics (통계학과)Journal Papers (저널논문_통계학과)
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