A Probabilistic Model for the Multidimensional Scaling of Proximity and Preference Data

David B. MacKay and Joseph L. Zinnes
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David B. MacKay: Indiana University
Joseph L. Zinnes: University of Illinois, Urbana

Marketing Science, 1986, vol. 5, issue 4, 325-344

Abstract: A probabilistic multidimensional scaling model that estimates both location and variance parameters for proximity and preference data is described and compared to a deterministic scaling model. Simulated and empirical choice data are used to compare models. Variance estimates from the probabilistic model are used to test a hypothesis about the homogeneity of stimulus perception under alternative modes of stimulus presentation.

Keywords: probabilistic model; preference data; proximity data; multidimensional scaling (search for similar items in EconPapers)
Date: 1986
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:5:y:1986:i:4:p:325-344

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