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Modeling Viewpoint Shifts in Probabilistic Choice

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  • Tomoya Okubo
  • Shin-ichi Mayekawa

Abstract

A number of mathematical models for overcoming intransitive choice have been proposed and tested in the literature of decision theory. This article presents the development of a new stochastic choice model based on multidimensional scaling. This allows decision-makers to have multiple viewpoints, whereas current multidimensional scaling models are based on the assumption that a subject or group of subjects has only one viewpoint. The implication of our model is that subjects make an intransitive choice because they are able to shift their viewpoint. This paper also presents the maximum likelihood estimation of the proposed model, and reanalyzes Tversky’s gamble experiment data. Copyright The Psychometric Society 2015

Suggested Citation

  • Tomoya Okubo & Shin-ichi Mayekawa, 2015. "Modeling Viewpoint Shifts in Probabilistic Choice," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 412-427, June.
  • Handle: RePEc:spr:psycho:v:80:y:2015:i:2:p:412-427
    DOI: 10.1007/s11336-013-9392-7
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    References listed on IDEAS

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    1. Loomes, Graham & Moffatt, Peter G & Sugden, Robert, 2002. "A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 24(2), pages 103-130, March.
    2. Birnbaum, Michael H. & Gutierrez, Roman J., 2007. "Testing for intransitivity of preferences predicted by a lexicographic semi-order," Organizational Behavior and Human Decision Processes, Elsevier, vol. 104(1), pages 96-112, September.
    3. repec:bla:econom:v:65:y:1998:i:260:p:581-98 is not listed on IDEAS
    4. DeSarbo, Wayne S. & Selin Atalay, A. & Blanchard, Simon J., 2009. "A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3217-3230, June.
    5. Birnbaum, Michael H. & Patton, Jamie N. & Lott, Melissa K., 1999. "Evidence against Rank-Dependent Utility Theories: Tests of Cumulative Independence, Interval Independence, Stochastic Dominance, and Transitivity, , , ," Organizational Behavior and Human Decision Processes, Elsevier, vol. 77(1), pages 44-83, January.
    6. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    7. Geert Soete & Suzanne Winsberg, 1993. "A latent class vector model for preference ratings," Journal of Classification, Springer;The Classification Society, vol. 10(2), pages 195-218, December.
    8. Budescu, David V. & Weiss, Wendy, 1987. "Reflection of transitive and intransitive preferences: A test of prospect theory," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(2), pages 184-202, April.
    9. Suzanne Winsberg & Geert De Soete, 2002. "A bootstrap procedure for mixture models: applied to multidimensional scaling latent class models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 18(4), pages 391-406, October.
    10. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    11. I. Böckenholt & W. Gaul, 1986. "Analysis of choice behaviour via probabilistic ideal point and vector models," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 2(4), pages 209-226.
    12. Wayne DeSarbo & Daniel Howard & Kamel Jedidi, 1991. "Multiclus: A new method for simultaneously performing multidimensional scaling and cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 121-136, March.
    13. Leo Goodman, 1979. "On the estimation of parameters in latent structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 44(1), pages 123-128, March.
    14. Iverson, G. & Falmagne, J. -C., 1985. "Statistical issues in measurement," Mathematical Social Sciences, Elsevier, vol. 10(2), pages 131-153, October.
    15. Joseph Bennett & William Hays, 1960. "Multidimensional unfolding: Determining the dimensionality of ranked preference data," Psychometrika, Springer;The Psychometric Society, vol. 25(1), pages 27-43, March.
    16. Wayne DeSarbo & Jaewun Cho, 1989. "A stochastic multidimensional scaling vector threshold model for the spatial representation of “pick any/n” data," Psychometrika, Springer;The Psychometric Society, vol. 54(1), pages 105-129, March.
    17. Geert Soete & Willem Heiser, 1993. "A latent class unfolding model for analyzing single stimulus preference ratings," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 545-565, December.
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