Abstract
Thurstonian models have proven useful in a wide range of applications because they can describe the multidimensional nature of choice objects and the effects of similarity and comparability in choice situations. Special cases of Thurstonian ranking models are formulated that impose different constraints on the covariance matrix of the objects’ utilities. In addition, mixture models are developed to account for individual differences in rankings. Two estimation procedures, maximum likelihood and generalized least squares, are discussed. To illustrate the approach, data from three ranking experiments are analyzed.
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Böckenholt, U. (1993). Applications of Thurstonian Models to Ranking Data. In: Fligner, M.A., Verducci, J.S. (eds) Probability Models and Statistical Analyses for Ranking Data. Lecture Notes in Statistics, vol 80. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2738-0_9
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DOI: https://doi.org/10.1007/978-1-4612-2738-0_9
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