BIVARIATE PROBIT, LOGIT, AND BURRIT ANALYSIS

Abstract

The problem of a mixture of two stimulants in a biological quantal assay is investigated from a mathematical standpoint. The basic assumption is made that the response region does not depend on biological considerations - i. e., given a specified mixture of stimulants z, the response region is defined by the point z' in the p-variate space where there are p stimulants under consideration; instead, the probability functions, themselves, may take on different forms. A general form is proposed and investigated. Three analytic models (one utilizing the bivariate normal distribution, one a bivariate logistic distribution developed by Gumbel (1961), and one a bivariate Burr distribution developed by this author) are employed in this investigation. The investigation includes the analysis of data, under the three analytic models, which had been classified by previous investigators as examples of synergistic action, simple similar action, independent action, and additive action. The residual analyses are included as well as the FORTRAN IV subroutines used in evaluating the functions, the partial derivatives and the weights.

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Document Details

Document Type
Technical Report
Publication Date
Aug 08, 1969
Accession Number
AD0694438

Entities

People

  • Frederick C. Durling

Organizations

  • Southern Methodist University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Bioassay
  • Computational Science
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Differential Equations
  • Equations
  • Factor Analysis
  • Information Science
  • Mathematical Models
  • Normal Distribution
  • Probability
  • Random Variables
  • Statistics
  • Toxicity
  • United States

Fields of Study

  • Mathematics

Readers

  • Molecular and Cellular Biochemistry
  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • Space