Interval Estimation for a Binomial Proportion

• Published in: Statistical science Vol. 16; no. 2; pp. 101 - 117
• Main Authors: Brown, Lawrence D., Cai, T. Tony, DasGupta, Anirban
• Format: Journal Article
• Language: English
• Published: Institute of Mathematical Statistics 01-05-2001; The Institute of Mathematical Statistics
• Subjects: Approximation; Bayes; binomial distribution; Binomial distributions; Binomials; Confidence interval; confidence intervals; coverage probability; Edgeworth expansion; expected length; Frequentism; Interval estimators; Jeffreys prior; Mathematical intervals; normal approximation; posterior; Probabilities; Proportions; Sample size
• ISSN: 0883-4237; 2168-8745
• DOI: 10.1214/ss/1009213286

We revisit the problem of interval estimation of a binomial proportion. The erratic behavior of the coverage probability of the standard Wald confidence interval has previously been remarked on in the literature (Blyth and Still, Agresti and Coull, Santner and others). We begin by showing that the chaotic coverage properties of the Wald interval are far more persistent than is appreciated. Furthermore, common textbook prescriptions regarding its safety are misleading and defective in several respects and cannot be trusted. This leads us to consideration of alternative intervals. A number of natural alternatives are presented, each with its motivation and context. Each interval is examined for its coverage probability and its length. Based on this analysis, we recommend the Wilson interval or the equal-tailed Jeffreys prior interval for small n and the interval suggested in Agresti and Coull for larger n. We also provide an additional frequentist justification for use of the Jeffreys interval.