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An approximate Bayesian up-down method for estimating a percentage point on a dose-response curve

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  • Hui Li
  • Robert Malkin

Abstract

While the up-down method for estimating a percentage point on a dose-response curve has received considerable attention, a general Bayesian solution to the up-down design and estimation has never been presented, probably due to its computational complexity both in design and use. This paper presents a theoretical approach for up-down experimental designs with unknown location and slope parameters, and a practical approach for their use. The simplex method is used to find the optimal starting dose level and step sizes that minimize the expected root mean square error for a fixed number of observations and a reduced number of step sizes. The Bayesian estimate is then approximated by a polynomial formula. The coefficients of the formula are also chosen using simplex minimization. Two example solutions are given with uniform-uniform and normal-gamma joint prior distributions, showing that the simplifying assumptions make the method far easier to use with only a marginal increase in expected root mean square error. We show how to adapt these prior distributions to a wide range of frequently encountered applications.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:5:p:579-587
    DOI: 10.1080/02664760050076416
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    References listed on IDEAS

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    1. 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.
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