1. Weighted confidence interval construction for binomial parameters.
- Author
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Olivier, Jake and May, Warren L.
- Subjects
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BINOMIAL distribution , *BINOMIAL theorem , *BINOMIAL equations , *QUANTITATIVE research , *CONFIDENCE intervals , *STATISTICAL hypothesis testing , *COMPARATIVE studies , *RESEARCH methodology , *MEDICAL cooperation , *RESEARCH , *EVALUATION research , *STATISTICAL models - Abstract
Confidence intervals, in general, have become an important aspect of reporting statistical results. In particular, interval estimators for binomial proportions have been studied extensively in recent literature. The large-sample Wald intervals are known to perform poorly, but the Wilson intervals have been shown to perform well in a variety of situations. One criticism is the relative difficulty of computing the Wilson or quadratic intervals in comparison to the Wald intervals. We offer a computational formula for the Wilson intervals that is a weighted estimator of the observed proportion, p, and that based on an uninformative prior, 1/2. This contribution enhances our understanding of the coverage behavior of the Wilson intervals. In addition, we contrast the Wilson intervals with other well-known intervals for the case of zero successes. [ABSTRACT FROM AUTHOR]
- Published
- 2006
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