Mean-Minimum Exact Confidence Intervals

摘要

This article introduces mean-minimum (MM) exact confidence intervals for a binomial probability. These intervals guarantee that both themean and theminimum frequentist coverage never drop below specified values. For example, an MM 95[ 93]% interval has mean coverage at least 95% and minimum coverage at least 93%. In the conventional sense, such an interval can be viewed as an exact 93% interval that hasmean coverage at least 95% or it can be viewed as an approximate 95% interval that has minimum coverage at least 93%. Graphical and numerical summaries of coverage and expected length suggest that the Blaker based MM exact interval is an attractive alternative to, even an improvement over, commonly recommended approximate and exact intervals, including the Agresti-Coull approximate interval, the Clopper-Pearson (CP) exact interval, and the more recently recommended CP-, Blaker-, and Sterne-based mean-coverageadjusted approximate intervals.