Interval estimation of the mean response in a log-regression model

Jianrong Wu, A. C.M. Wong, Wei Wei

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


A standard approach to the analysis of skewed response data with concomitant information is to use a log-transformation to normalize the distribution of the response variable and then conduct a log-regression analysis. However, the mean response at original scale is often of interest. El-Shaarawi and Viveros developed an interval estimation of the mean response of a log-regression model based on large sample theory. There is however very little information available in the literature on constructing such estimates when the sample size is small. In this paper, we develop a small-sample corrected interval by using the likelihood-based inference method developed by Barndorff-Nielson and Fraser et al. Simulation results show that the proposed interval provides almost exact coverage probability, even for small samples.

Original languageEnglish
Pages (from-to)2125-2135
Number of pages11
JournalStatistics in Medicine
Issue number12
StatePublished - Jun 30 2006


  • Confidence interval
  • Coverage probability
  • Log-regression model
  • Mean response
  • R*-formula

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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