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Dealing with heterogeneity in ordinal responses

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  • Stefania Capecchi

    (University of Naples Federico II)

  • Domenico Piccolo

    (University of Naples Federico II)

Abstract

In sample surveys where people are asked to express their personal opinions it is conceivable to register a high level of indecision among respondents and this circumstance generates sub-optimal statistical analyses caused by large heterogeneity in the responses. In this paper, we discuss a model belonging to the class of generalized cub models which is worthwhile for this kind of surveys. Then, we examine some real case studies where the observed heterogeneity and the subjects’ indecision can be analyzed with the proposed approach leading to convincing interpretations. A comparison with more consolidated models and some concluding remarks end the paper.

Suggested Citation

  • Stefania Capecchi & Domenico Piccolo, 2017. "Dealing with heterogeneity in ordinal responses," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2375-2393, September.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0393-3
    DOI: 10.1007/s11135-016-0393-3
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    1. Blanchflower, David G. & Oswald, Andrew J., 2004. "Well-being over time in Britain and the USA," Journal of Public Economics, Elsevier, vol. 88(7-8), pages 1359-1386, July.
    2. William Gehrlein & Dominique Lepelley & Issofa Moyouwou, 2015. "Voters’ preference diversity, concepts of agreement and Condorcet’s paradox," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2345-2368, November.
    3. Alesina, Alberto & Di Tella, Rafael & MacCulloch, Robert, 2004. "Inequality and happiness: are Europeans and Americans different?," Journal of Public Economics, Elsevier, vol. 88(9-10), pages 2009-2042, August.
    4. D'Elia, Angela & Piccolo, Domenico, 2005. "A mixture model for preferences data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 917-934, June.
    5. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    6. Hsin-Hung Wu & Jiunn-I Shieh, 2010. "Quantifying uncertainty in applying importance-performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(5), pages 997-1003, August.
    7. Nanak Kakwani & Shahid Khandker & Hyun H. Son, 2004. "Pro-poor growth: concepts and measurement with country case studies," Working Papers 1, International Policy Centre for Inclusive Growth.
    8. Tamar Gadrich & Emil Bashkansky & Ričardas Zitikis, 2015. "Assessing variation: a unifying approach for all scales of measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1145-1167, May.
    9. Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
    10. Ravallion, Martin, 2004. "Pro-poor growth : A primer," Policy Research Working Paper Series 3242, The World Bank.
    11. Guy Moors, 2008. "Exploring the effect of a middle response category on response style in attitude measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 42(6), pages 779-794, December.
    12. Molenberghs, Geert & Verbeke, Geert, 2007. "Likelihood Ratio, Score, and Wald Tests in a Constrained Parameter Space," The American Statistician, American Statistical Association, vol. 61, pages 22-27, February.
    13. Bruno Trezzini, 2013. "A measure of multidimensional polarization for categorical diversity data," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 313-333, January.
    14. William Gehrlein & Florenz Plassmann, 2014. "A comparison of theoretical and empirical evaluations of the Borda Compromise," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(3), pages 747-772, October.
    15. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    16. Maria Iannario, 2012. "Modelling shelter choices in a class of mixture models for ordinal responses," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 1-22, March.
    17. KANKARASH Milosh & MOORS Guy, 2007. "Heterogeneity in solidarity attitudes in Europe. Insights from a multiple-group latent-class factor approach," IRISS Working Paper Series 2007-06, IRISS at CEPS/INSTEAD.
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    Cited by:

    1. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    2. Capecchi, Stefania & Amato, Mario & Sodano, Valeria & Verneau, Fabio, 2019. "Understanding beliefs and concerns towards palm oil: Empirical evidence and policy implications," Food Policy, Elsevier, vol. 89(C).
    3. Rosaria Simone, 2021. "An accelerated EM algorithm for mixture models with uncertainty for rating data," Computational Statistics, Springer, vol. 36(1), pages 691-714, March.
    4. Stefania Capecchi & Rosaria Simone, 2019. "A Proposal for a Model-Based Composite Indicator: Experience on Perceived Discrimination in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 95-110, January.
    5. Stefania Capecchi & Marta Meleddu & Manuela Pulina, 2019. "Quality evaluation and preferences of healthcare services: the case of telemedicine in Sardinia," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2339-2351, September.
    6. Stefania Capecchi & Romina Gambacorta & Rosaria Simone & Domenico Piccolo, 2024. "Modelling cognitive response patterns to survey questions using the class of CUB models," Questioni di Economia e Finanza (Occasional Papers) 885, Bank of Italy, Economic Research and International Relations Area.

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