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Robustness of interval estimation of the 90% effective dose: Bootstrap resampling and some large-sample parametric methods

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  • Yangxin Huang

Abstract

Interval estimation of the x th effective dose (ED x ), where x is a prespecified percentage, has been the focus of interest of a number of recent studies, the majority of which have considered the case in which a logistic dose-response curve is correctly assumed. In this paper, we focus our attention upon the 90% effective dose (ED 90 ) and consider the situation in which the assumption of a logistic dose-response curve is incorrect. Specifically, we consider three classes of true model: the probit, the cubic logistic and the asymmetric Aranda-Ordaz models. We investigate the robustness of four large sample parametric methods of interval construction and four methods based upon bootstrap resampling.

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  • 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.
    • Handle: RePEc:taf:japsta:v:29:y:2002:i:7:p:1071-1081
    DOI: 10.1080/0266476022000006748
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    References listed on IDEAS

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    1. Byron J. T. Morgan, 1985. "The Cubic Logistic Model for Quantal Assay Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(2), pages 105-113, June.
    2. 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.
    3. Yangxin Huang Simon & P. J. Kirby Peter & Harris John & C. Dearden, 2000. "Interval estimation of the 90% effective dose: A comparison of bootstrap resampling methods with some large-sample approaches," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(1), pages 63-73.
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