Likelihood-based confidence intervals for a log-normal mean

Jianrong Wu, A. C.M. Wong, Guoyong Jiang

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


To construct a confidence interval for the mean of a log-normal distribution in small samples, we propose likelihood-based approaches - the signed log-likelihood ratio and modified signed log-likelihood ratio methods. Extensive Monte Carlo simulation results show the advantages of the modified signed log-likelihood ratio method over the signed log-likelihood ratio method and other methods. In particular, the modified signed log-likelihood ratio method produces a confidence interval with a nearly exact coverage probability and highly accurate and symmetric error probabilities even for extremely small sample sizes. We then apply the methods to two sets of real-life data.

Original languageEnglish
Pages (from-to)1849-1860
Number of pages12
JournalStatistics in Medicine
Issue number11
StatePublished - Jun 15 2003


  • Confidence interval
  • Coverage probability
  • Log-normal mean
  • Parametric bootstrap
  • Signed log-likelihood ratio
  • r*-formula

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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