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A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification

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  • Simon Blanchard

    ()

  • Wayne DeSarbo

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Abstract

We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic example and a consumer psychology study involving categories of restaurant brands illustrate how the application of the proposed methodology to the new sorting task can account for a variety of categorization phenomena including multiple category memberships and for heterogeneity through individual differences in the saliency of latent category structures. Copyright The Psychometric Society 2013

Suggested Citation

  • Simon Blanchard & Wayne DeSarbo, 2013. "A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification," Psychometrika, Springer;The Psychometric Society, vol. 78(2), pages 322-340, April.
  • Handle: RePEc:spr:psycho:v:78:y:2013:i:2:p:322-340
    DOI: 10.1007/s11336-012-9315-z
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    References listed on IDEAS

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    1. Moreau, C Page & Markman, Arthur B & Lehmann, Donald R, 2001. " "What Is It?" Categorization Flexibility and Consumers' Responses to Really New Products," Journal of Consumer Research, Oxford University Press, vol. 27(4), pages 489-498, March.
    2. Loken, Barbara & Ward, James C, 1990. " Alternative Approaches to Understanding the Determinants of Typicality," Journal of Consumer Research, Oxford University Press, vol. 17(2), pages 111-126, September.
    3. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    4. Kaye Basford & Geoffrey McLachlan, 1985. "The mixture method of clustering applied to three-way data," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 109-125, December.
    5. Simon Blanchard & Wayne DeSarbo & A. Atalay & Nukhet Harmancioglu, 2012. "Identifying consumer heterogeneity in unobserved categories," Marketing Letters, Springer, vol. 23(1), pages 177-194, March.
    6. J. Carroll & Phipps Arabie, 1983. "Indclus: An individual differences generalization of the adclus model and the mapclus algorithm," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 157-169, June.
    7. Simon Blanchard & Daniel Aloise & Wayne DeSarbo, 2012. "The Heterogeneous P-Median Problem for Categorization Based Clustering," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 741-762, October.
    8. J. Carroll & Linda Clark & Wayne DeSarbo, 1984. "The representation of three-way proximity data by single and multiple tree structure models," Journal of Classification, Springer;The Classification Society, vol. 1(1), pages 25-74, December.
    9. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-238, July-Sept.
    10. Suzanne Winsberg & J. Douglas Carroll, 1989. "A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model," Psychometrika, Springer;The Psychometric Society, vol. 54(2), pages 217-229, June.
    11. Kurt A. Carlson & Margaret G. Meloy & J. Edward Russo, 2006. "Leader-Driven Primacy: Using Attribute Order to Affect Consumer Choice," Journal of Consumer Research, Oxford University Press, vol. 32(4), pages 513-518, March.
    12. Vermunt, Jeroen K., 2007. "A hierarchical mixture model for clustering three-way data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5368-5376, July.
    13. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    14. J. Ramsay, 1977. "Maximum likelihood estimation in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 241-266, June.
    15. T. Klastorin, 1980. "Merging groups to maximize object partition comparison," Psychometrika, Springer;The Psychometric Society, vol. 45(4), pages 425-433, December.
    16. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.
    17. Richard Degerman, 1982. "Ordered binary trees constructed through an application of Kendall's tau," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 523-527, December.
    18. Venkatram Ramaswamy & Eugene W. Anderson & Wayne S. DeSarbo, 1994. "A Disaggregate Negative Binomial Regression Procedure for Count Data Analysis," Management Science, INFORMS, vol. 40(3), pages 405-417, March.
    19. John Daws, 1996. "The analysis of free-sorting data: Beyond pairwise cooccurrences," Journal of Classification, Springer;The Classification Society, vol. 13(1), pages 57-80, March.
    20. Chih-Chien Yang & Chih-Chiang Yang, 2007. "Separating Latent Classes by Information Criteria," Journal of Classification, Springer;The Classification Society, vol. 24(2), pages 183-203, September.
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    Cited by:

    1. Santi, Éverton & Aloise, Daniel & Blanchard, Simon J., 2016. "A model for clustering data from heterogeneous dissimilarities," European Journal of Operational Research, Elsevier, vol. 253(3), pages 659-672.
    2. Rebecca Hamilton & Debora Thompson & Zachary Arens & Simon Blanchard & Gerald Häubl & P. Kannan & Uzma Khan & Donald Lehmann & Margaret Meloy & Neal Roese & Manoj Thomas, 2014. "Consumer substitution decisions: an integrative framework," Marketing Letters, Springer, vol. 25(3), pages 305-317, September.

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