Joint Estimation of Binomial Proportions

Kent Riggs and Stephanie Weatherford

International Journal of Statistics and Probability, 2025, vol. 12, issue 2, 8

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.

Date: 2025
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