Joint Estimation of Binomial Proportions

K. Riggs, Stephanie Weatherford
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Abstract

Interval estimation of a binomial proportion has had a consistent presence in the statistical literature through the years. Many interval procedures have been developed for a single proportion as well as for the difference of two proportions. However, little work has been conducted on the joint estimation of two binomial proportions. In this paper, we construct four confidence regions for two binomial proportions based on three statistics: the Wald (W), adjusted Wald (W*), score (S), and likelihood ratio (LR) statistics. Once the regions have been established, we compare their coverage probabilities and average areas for different parameter and sample size configurations. For small-to-moderate sample sizes, this paper finds that the three regions based on the W*, S, and LR statistics have good coverage properties, with the score region usually having the smallest average area. Finally, we apply these four confidence regions to some real data in veterinary science and medicine for the joint estimation of important proportions.
二项比例的联合估计
多年来,二项式比例的区间估计在统计文献中一直存在。对于单一比例以及两个比例的差异,已经开发了许多区间程序。然而,很少有人对两个二项式比例进行联合估计。在本文中,我们基于三个统计量为两个二项式比例构建了四个置信区:Wald(W)、调整后的Wald(W*)、分数(S)和似然比(LR)统计量。一旦建立了区域,我们就比较不同参数和样本量配置的覆盖概率和平均面积。对于小到中等样本量,本文发现基于W*、S和LR统计的三个区域具有良好的覆盖特性,其中得分区域通常具有最小的平均面积。最后,我们将这四个置信区间应用于兽医学和医学中的一些真实数据,以联合估计重要比例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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