An Inferential Approach to the Bioassay Design Problem.

Abstract

The Bioassay design problem may usefully be considered within an inferential framework, rather than by reference to a formal decision theoretic procedure based upon a number of special assumptions. Three graphical techniques are described to assist the user's selection of new design points. Firstly, a plot, against dose level, of the predictive probability of the death of the next rat will help the user to choose design points relating to particular regions of LD values; comparison with the maximum likelihood estimate of the response curve leads to informal stopping rules. Secondly, new approximations, to the posterior density of the effective dose, are proposed, for each LD value. These are related to the marginal likelihood ideas of Sprott and Kalbfleisch. Thirdly, mixtures of these densities leads to design measures for the distribution of future dose levels. These seem to make criteria like D-optimality rather tangential to the real design issue. The ideas are illustrated graphically by reference to a fertility example due to Bliss.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1982
Accession Number
ADA120986

Entities

People

  • Tom Leonard

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Bayesian Networks
  • Bioassay
  • Classification
  • Contracts
  • Data Science
  • Distribution Functions
  • Fertility
  • Gaussian Distributions
  • Information Science
  • Mathematics
  • Normal Distribution
  • Observation
  • Probability
  • Random Variables
  • Statistical Inference
  • Statistics
  • United States

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Systems Analysis and Design
  • Toxicology/Environmental Toxicology