The Relationship between the Number of Factors and Size of an Experiment.

Abstract

If the number of factors in an experiment is increased, does it necessarily follow that the size of the experiment must increase to achieve a satisfactory analysis? In some common situations the answer is No. The present paper discusses a model suggested by medical diagnostic problems in which the answer is Yes: indeed, the increase in size is exponentially fast. The conclusion is drawn that statisticians should be cautions before embarking on the study of data with large numbers of factors because the data may be inadequate for a sensible analysis. The basic, mathematical tool is the Kullback-Leibler number which measures the discrimination between the possibilities. Calculation of these numbers uses interactions, forming a basis for all the effects that might occur. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1981
Accession Number
ADA103877

Entities

People

  • D. V. Lindley

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Agreements
  • Bayes Theorem
  • Combinatorial Analysis
  • Computational Complexity
  • Contrast
  • Data Analysis
  • Data Sets
  • Discrimination
  • Equations
  • Experimental Design
  • Mathematical Analysis
  • Mathematics
  • Probability
  • Statistical Analysis
  • Statistics
  • Theorems
  • United States

Readers

  • Regression Analysis.
  • Systems Analysis and Design