Better Binomial Confidence Intervals

被引：14

作者：

Reed, James F., III ^{[1
,2
]}

机构：

[1] Lehigh Valley Hosp & Hlth Network, Hlth Studies, Allentown, PA 18103 USA

[2] Lehigh Valley Hosp & Hlth Network, Res, Allentown, PA USA

来源：

JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2007年 / 6卷 / 01期

关键词：

Binomial distribution; confidence intervals; coverage probability; Wald method; Clopper-Pearson Method; Score Method; Agresti-Coull method;

D O I：

10.22237/jmasm/1177992840

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The construction of a confidence interval for a binomial parameter is a basic analysis in statistical inference. Most introductory statistics textbook authors present the binomial confidence interval based on the asymptotic normality of the sample proportion and estimating the standard error - the Wald method. For the one sample binomial confidence interval the Clopper-Pearson exact method has been regarded as definitive as it eliminates both overshoot and zero width intervals. The Clopper-Pearson exact method is the most conservative and is unquestionably a better alternative to the Wald method. Other viable alternatives include Wilson's Score, the Agresti-Coull method, and the Borkowf SAIFS-z.

引用

页码：153 / 161

页数：9

共 18 条

[1] Dealing with discreteness: making 'exact' confidence intervals for proportions, differences of proportions, and odds ratios more exact [J].