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Selection of Dose Levels for Estimating a Percentage Point of a Logistic Quantal Response Curve

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  • Robert K. Tsutakawa

Abstract

Experimental designs are presented for estimating an extreme percentage point of a logistic distribution when the observations are quantal responses and the location and scale parameters are unknown. The method is based on a prior distribution of the parameters and a predicted value of the posterior variance. The paper is an extension of an earlier article (Tsutakawa, 1972) for the case when the scale parameter is known.

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  • Robert K. Tsutakawa, 1980. "Selection of Dose Levels for Estimating a Percentage Point of a Logistic Quantal Response Curve," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 25-33, March.
    • Handle: RePEc:bla:jorssc:v:29:y:1980:i:1:p:25-33
    DOI: 10.2307/2346406
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    Cited by:

    1. Zacks, S. & Rogatko, A. & Babb, J., 1998. "Optimal Bayesian-feasible dose escalation for cancer phase I trials," Statistics & Probability Letters, Elsevier, vol. 38(3), pages 215-220, June.
    2. Hanemann, W. Michael & Kanninen, Barbara, 1996. "The Statistical Analysis Of Discrete-Response Cv Data," CUDARE Working Papers 25022, University of California, Berkeley, Department of Agricultural and Resource Economics.
    3. Yangxin Huang, 2003. "Selection of number of dose levels and its robustness for binary response data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1135-1146.
    4. Silvio S. Zocchi & Anthony C. Atkinson, 1999. "Optimum Experimental Designs for Multinomial Logistic Models," Biometrics, The International Biometric Society, vol. 55(2), pages 437-444, June.
    5. Linda M. Haines & Inna Perevozskaya & William F. Rosenberger, 2003. "Bayesian Optimal Designs for Phase I Clinical Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 591-600, September.
    6. Hui Li & Robert Malkin, 2000. "An approximate Bayesian up-down method for estimating a percentage point on a dose-response curve," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(5), pages 579-587.

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