Closed form prediction intervals applied for disease counts

Hsiuying Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


The prediction interval is an important tool in medical applications for predicting the number of times a disease will occur in a population. The performance of the existing prediction intervals, however, is unsatisfactory when the true proportion is near a boundary. Since the true proportion can be very small in real applications, in this article, we propose improved prediction intervals with better coverage probability than the existing methods. Their predictive distributions are compared in terms of the Kullback-Leibler distance and the intervals are compared using a hearing screening medical example.

Original languageEnglish
Pages (from-to)250-256
Number of pages7
JournalAmerican Statistician
Issue number3
StatePublished - 1 May 2010


  • Binomial distribution
  • Coverage probability
  • Prediction interval
  • Predictive distribution


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