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Theory and Decision

, Volume 9, Issue 1, pp 109–114 | Cite as

What can the regression model of human judgment learn from multi-attribute decision theory?

  • John Fountain
Discussion

Abstract

Zeleny's recent conjecture that multi-attribute decision theory may help to overcome the inadequacies of the linear regression model is incorrect. Recognition of the information processing advantages inherent in multiple -attribute decision situations combined with a requirement of transitivity itself implies linear objective functions. This follows from some recent developments by a psychologist and an economist in the analysis of individual and collective decision processes, developments which do not take as their starting point the paradigm of choice offered in utility theory.

Keywords

Linear Regression Objective Function Regression Model Information Processing Decision Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Cochrane, J. L. and Zeleny, M. (1973), Multiple Criteria Decision Making. University of South Carolina Press, Columbia, South Carolina.Google Scholar
  2. Fountain, J. (1976), Voting Processes Incorporating Intensities of Preference: A Possibility Result, Discussion Paper, Economics Department, University of Canterbury, Christchurch, New Zealand.Google Scholar
  3. Fountain, J. (1977), ‘An Experiment and Bayesian Inferences Concerning some Stochastic Choice Theories’, Discussion Paper, Economics Department, University of Canterbury, Christchurch, New Zealand.Google Scholar
  4. Tversky, A. (1969), ‘Intransitivity of Preference’, Psychological Review 76, 00–00.Google Scholar
  5. Zeleny, M. (1976), ‘On the Inadequacy of the Regression Paradigm used in the Study of Human Judgment’ Theory and Decision 7, pp. 57–66.Google Scholar

Copyright information

© D. Reidel Publishing Company 1978

Authors and Affiliations

  • John Fountain
    • 1
  1. 1.Canterbury UniversityUK

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