Volume 12, Issue 4 (Vol.12, No.4 2017)                   irje 2017, 12(4): 55-63 | Back to browse issues page

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Hamzeh S, Soltanian A, Faradmal J. Confidence Interval Estimation of Proportion Near Zero or One: A Modeling Secondary Study. irje. 2017; 12 (4) :55-63
URL: http://irje.tums.ac.ir/article-1-5621-en.html
1- MSc of Biostatistics, Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran کارشناسی ارشد گروه آمار زیستی و اپیدمیولوژی، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران
2- Associate of Biostatistics, Department of Biostatistics, School of Public Health, Modeling of non-communicable diseases research center, Hamadan University of Medical Sciences, Hamadan, Iran دانشیار آمار زیستی، گروه آمار زیستی، مرکز تحقیقات مدل‌سازی بیماری‌های غیر واگیر، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران , soltanian@umsha.ac.ir
3- Associate of Biostatistics, Department of Biostatistics, School of Public Health, Modeling of non-communicable diseases research center, Hamadan University of Medical Sciences, Hamadan, Iran دانشیار آمار زیستی، گروه آمار زیستی، مرکز تحقیقات مدل‌سازی بیماری‌های غیر واگیر، دانشکده بهداشت، دانشگاه علوم پزشکی همدان، همدان، ایران
Abstract:   (3433 Views)

Background and Objectives: When computing a confidence interval for a binomial proportion p, one must choose an exact interval that has a coverage probability of at least 1-α for all values of p. In this study, we compared the confidence intervals of Clopper-Pearson, Wald, Wilson, and double ArcSin transformation in terms of maintaining a constant nominal type I error.

Methods: Simulations were used to compare four methods of estimating a confidence interval, including the Clopper-Pearson, Wald, Wilson, and double ArcSic. The data were generated from the binomial and Poison distribution with parameters p, n and µ=np, 1000 were produced . Type I error of each method was calculated per simulation. The above methods were used to estimate confidence intervals in a meta-analysis study.

Results: The results of the simulation study showed that double ArcSin keep confidence interval at [0,1], but for some proportion has high type I error or low coverage probability. The Clopper–Pearson interval guarantees that the coverage probability is always equal to or above the nominal confidence level for any fixed p.

Conclusion: This study showed that confidence interval estimations the Clopper-Pearson than other methods of calculating the type I error fixed and smaller.

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Type of Study: Research | Subject: General
Received: 2017/01/30 | Accepted: 2017/01/30 | Published: 2017/01/30

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