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Testing a Mixture of Rank Preference Models on Judges' Scores in Paris and Princeton*

Published online by Cambridge University Press:  20 August 2015

Jeffrey C. Bodington*
Affiliation:
Bodington & Company, 50 California Street #630, San Francisco, CA 94111; e-mail: jcb@bodingtonandcompany.com.

Abstract

Rank preference and mixture models have been employed to evaluate the ranks assigned by consumers in taste tests of beans, cheese, crackers, salad dressings, soft drinks, sushi, animal feed, and wine. In many wine tastings, including the famous 1976 Judgment of Paris and the 2012 Judgment of Princeton, judges assign scores rather than ranks, and those scores often include ties. This article advances the application of ranking and mixture models to wine-tasting results by modifying the established use of a Plackett-Luce rank preference model to accommodate scores and ties. The modified model is tested and then employed to evaluate the Paris and Princeton wine-tasting results. Test results show that the mixture model is an accurate predictor of observed rank densities. Results for Paris and Princeton show that the group preference orders implied by the mixture model are highly correlated with the orders implied by widely employed rank-sum methods. However, the mixture model satisfies choice axioms that rank-sum methods do not, it yields an estimate of the proportion of scores that appear to be assigned randomly, and it also yields a preference order based on nonrandom preferences that tasters appear to hold in common. (JEL Classifications: A10, C00, C10, C12, D12)

Type
Articles
Copyright
Copyright © American Association of Wine Economists 2015 

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Footnotes

*

The author thanks an anonymous reviewer for his or her helpful comments. All remaining errors and omissions are the responsibility of the author alone.

References

Arrow, K.J. (1963). Social Choice and Individual Values. 2nd ed. New York: John Wiley & Sons.Google Scholar
Ashenfelter, O., and Quandt, R.E (1999). Analyzing a wine tasting statistically. Chance, 12, 1620.Google Scholar
Ashenfelter, O., and Storchmann, K. (2012). Editorial: The Judgment of Princeton and other articles. Journal of Wine Economics, 7(2), 139142.Google Scholar
Ashton, R.H. (2014). Nothing good ever came from New Jersey: Expectations and the sensory perception of wine. Journal of Wine Economics, 9(3), 304319.Google Scholar
Benter, W. (1994). Computer-based horse race handicapping and wagering systems: A report. In Ziemba, W.T., Lo, V.S., and Haush, D.B. (eds.), Efficiency of Racetrack Betting Markets. San Diego: Academic Press, 183198.Google Scholar
Bockenholt, U. (1992). Thurstonian representation for partial ranking data. British Journal of Mathematical and Statistical Psychology, 45, 3149.Google Scholar
Bodington, J. (2012). 804 Tastes: Evidence on randomness, preferences and value from blind tastings. Journal of Wine Economics, 7(2), 181191.Google Scholar
Bodington, J. (2015). Evaluating wine-tasting results and randomness with a mixture of rank preference models. Journal of Wine Economics, 10(1), 3146.Google Scholar
Cao, J. (2014). Quantifying randomness versus consensus in wine quality ratings. Journal of Wine Economics, 9(2), 202213.Google Scholar
Chen, W. (2014). How to Order Sushi. PhD dissertation, Harvard University.Google Scholar
Cicchetti, D.V. (2006). The Paris 1976 wine tasting revisited once more: Comparing ratings of consistent and inconsistent tasters. Journal of Wine Economics, 1(2), 125140.Google Scholar
Cicchetti, D.V. (2014). Blind tasting of South African wines: A tale of two methodologies. American Association of Wine Economists. AAWE Working Paper No. 164.Google Scholar
Cleaver, G., and Wedel, M. (2001). Identifying random-scoring respondent in sensory research using finite mixture regression results. Food Quality and Preference, 12, 373384.CrossRefGoogle Scholar
Critchlow, D.E. (1980). Metric Methods for Analyzing Partially Ranked Data. New York: Springer.Google Scholar
De Bruin, W. (2005). Save the last dance for me: Unwanted serial position effects in jury evaluations. Acta Psychologica, 118(3), 245260.Google Scholar
Dempster, A.P., Laird, N.M., and Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B, 39(1), 138.Google Scholar
Filipello, F. (1955). Small panel taste testing of wine. American Journal of Enology, 6(4), 2632.Google Scholar
Filipello, F. (1956). Factors in the analysis of mass panel wine-preference data. Food Technology, 10, 321326.Google Scholar
Filipello, F. (1957). Organoleptic wine-quality evaluation II: Performance of judges. Food Technology, 11, 5153.Google Scholar
Filipello, F., and Berg, H.W. (1958). The present status of consumer tests on wine. Paper presented at the Ninth Annual Meeting of the American Society of Enologists, Asilomar, Pacific Grove, California, June 27–28.Google Scholar
Ginsburgh, V., and Zang, I. (2012). Shapley ranking of wines. Journal of Wine Economics, 7(2), 169180.CrossRefGoogle Scholar
Gormley, I.C., and Murphy, T.B. (2007). A latent space model for rank data. In Airoldi, E., Blei, D.M., Fienberg, S.E., Goldenberg, A., Xing, E.P., and Zheng, A.X. (eds.), Statistical Network Analysis: Models, Issues and New Directions. Berlin: Springer, 90102.Google Scholar
Gormley, I.C., and Murphy, T.B. (2008). A mixture of experts model for rank data with applications in election studies. Annals of Applied Statistics, 2(4), 14521477.Google Scholar
Hulkower, N.D. (2009). The Judgment of Paris according to Borda. Journal of Wine Research, 20(3), 171182.Google Scholar
Kidwell, P., Lebanon, G., and Cleveland, W.S. (2008). Visualizing incomplete and partially ranked data. IEEE Transactions on Visualization and Computer Graphics, 14(6) 13561364.Google Scholar
Lindley, D.V. (2006). Analysis of a wine tasting. Journal of Wine Economics, 1(1), 3341.Google Scholar
Luce, R. D. (1977). The choice axiom after twenty years. Journal of Mathematical Psychology, 15 (3), 215233.Google Scholar
Mantonakis, A., Rodero, P., Lesschaeve, I., and Hastie, R. (2009). Order in choice: Effects of serial position on preferences. Psychological Science, 20(11), 13091312.Google Scholar
Marden, J.I. (1995). Analyzing and Modeling Rank Data. London: Chapman & Hall.Google Scholar
Masson, J., and Aurier, P. (2015). Should it be told or tasted? Impact of sensory versus nonsensory cues on the categorization of low-alcohol wines. Journal of Wine Economics, 10(1), 6274.CrossRefGoogle Scholar
McLachlan, G., and Peel, D. (2000). Finite Mixture Models. New York: John Wiley & Sons.Google Scholar
Mengersen, K.L., Robert, C.P., and Titterington, D.M. (2011). Mixtures: Estimation and Application. New York: John Wiley & Sons.Google Scholar
Olkin, I., Lou, Y., Stokes, L. and Cao, J. (2015). Analyses of wine-tasting data: A tutorial. Journal of Wine Economics, 10(1), 430.Google Scholar
Plackett, R.L. (1975). The analysis of permutations. Applied Statistics, 24(2), 193202.CrossRefGoogle Scholar
Quandt, R.E. (2006). Measurement and inference in wine tasting. Journal of Wine Economics, 1(1), 730.Google Scholar
Quandt, R.E. (2012). Comments on the Judgment of Princeton. Journal of Wine Economics, 2(7), 152154.Google Scholar
Taber, G.M. (2005). Judgment of Paris: California vs. France and the Historic 1976 Paris Tasting That Revolutionized Wine. New York: Scribner.Google Scholar
Taber, G.M. (2012). The Judgment of Princeton. Journal of Wine Economics, 2(7), 143151.Google Scholar
Theusen, K.F. (2007). Analysis of ranked preference data. Master's thesis, Technical University of Denmark, Kongens Lyngby, Denmark.Google Scholar
Vigneau, E., Courcoux, P., and Semenou, M. (1999). Analysis of ranked preference data using latent class models. Food Quality and Preference, 10(3), 201207.Google Scholar
Ward, D.L. (2012). A graphical and statistical analysis of the Judgment of Princeton wine tasting. Journal of Wine Economics, 7(2), 155168.CrossRefGoogle Scholar