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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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    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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