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September, 1983 Bayesian Bioassay Design
Lynn Kuo
Ann. Statist. 11(3): 886-895 (September, 1983). DOI: 10.1214/aos/1176346254

Abstract

A Bayesian treatment of the quantal bioassay design problem is given. It is assumed that the potency curve is a Dirichlet random distribution $F$ with parameter $\alpha(t) = MF_0(t)$, and that $n_1, \cdots, n_L$ animals are treated at drug levels $t_1, \cdots, t_L$ respectively. The optimal design levels $t_1, \cdots, t_L$ that minimize the Bayes risk for weighted integrated quadratic loss functions are found in the following cases: (i) $L = 1$ and the weight function arbitrary; (ii) uniform prior guess, uniform weight and two animals treated; and (iii) uniform weight and $L$ arbitrary, but $M \rightarrow 0$. These results disprove a conjecture of Antoniak.

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Lynn Kuo. "Bayesian Bioassay Design." Ann. Statist. 11 (3) 886 - 895, September, 1983. https://doi.org/10.1214/aos/1176346254

Information

Published: September, 1983
First available in Project Euclid: 12 April 2007

zbMATH: 0521.62086
MathSciNet: MR707938
Digital Object Identifier: 10.1214/aos/1176346254

Subjects:
Primary: 62K05
Secondary: 62C10, 62P10

Rights: Copyright © 1983 Institute of Mathematical Statistics

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Vol.11 • No. 3 • September, 1983
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