Coverage-adjusted confidence intervals for a binomial proportion

Abstract

We consider the classic problem of interval estimation of a proportion $p$ based on binomial sampling. The "exact" Clopper-Pearson confidence interval for $p$ is known to be unnecessarily conservative. We propose coverage-adjustments of the Clopper-Pearson interval using prior and posterior distributions of $p$. The adjusted intervals have improved coverage and are often shorter than competing intervals found in the literature. Using new heatmap-type plots for comparing confidence intervals, we find that the coverage-adjusted intervals are particularly suitable for $p$ close to 0 or 1.

arXiv comment20 pages, 10 figures, 2 tables

Cited by in corpus (3)

• The cost of using exact confidence intervals for a binomial proportion
• Exact confidence intervals and hypothesis tests for parameters of discrete distributions
• On split sample and randomized confidence intervals for binomial proportions