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Interval estimation of the median effective dose for a logistic dose-response curve

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  • Peter Harris
  • Mark Hann
  • Simon Kirby
  • John Dearden

Abstract

In 1986, Williams showed how, assuming a logistic dose-response curve, one can construct a confidence interval for the median effective dose from the asymptotic likelihood ratio test. He gave reasons for preferring this likelihood ratio interval to the established interval calculated by applying Fieller's theorem to the maximum-likelihood estimates. Here, we assess the impact of applying a Bartlett adjustment to the likelihood ratio statistic and introduce the score test as an alternative approach for constructing a confidence interval for the median effective dose.

Suggested Citation

  • Peter Harris & Mark Hann & Simon Kirby & John Dearden, 1999. "Interval estimation of the median effective dose for a logistic dose-response curve," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 715-722.
    • Handle: RePEc:taf:japsta:v:26:y:1999:i:6:p:715-722
    DOI: 10.1080/02664769922151
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    References listed on IDEAS

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    1. Moulton, Lawrence H. & Weissfeld, Lisa A. & St. Laurent, Roy T., 1993. "Bartlett correction factors in logistic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 15(1), pages 1-11, January.
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    Cited by:

    1. Huang, Yangxin, 2001. "Interval estimation of the ED50 when a logistic dose-response curve is incorrectly assumed," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 525-537, June.
    2. Huang, Yangxin, 2002. "On large-sample parametric approaches for interval estimation of the ED90," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 527-537, September.
    3. Yangxin Huang, 2002. "Robustness of interval estimation of the 90% effective dose: Bootstrap resampling and some large-sample parametric methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 1071-1081.

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