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An Inflated Model to Account for Large Heterogeneity in Ordinal Data

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Data Science

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Abstract

In sample surveys where people are asked to express their opinions, a high level of indecision among respondents may generate sub-optimal statistical analyses caused by large heterogeneity in the responses. We discuss a model belonging to the class of generalized cub models that is suitable for this kind of surveys. Then, we examine a real case study where the observed heterogeneity as well as respondents’ indecision can be analyzed within the theoretical framework of the proposed model leading to convincing interpretations. A comparison with current literature and some concluding remarks end the paper.

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Acknowledgements

This work has been realized within the FIRB2012 project (code RBFR12SHVV) at University of Perugia and the frame of Programme STAR (CUP E68C13000020003) at University of Naples Federico II, financially supported by UniNA and Compagnia di San Paolo.

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Authors and Affiliations

  1. Department of Political Sciences, University of Naples Federico II, Via L. Rodinò 22, I-80138, Naples, Italy

    Stefania Capecchi, Rosaria Simone & Domenico Piccolo

Authors
  1. Stefania Capecchi
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  2. Rosaria Simone
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  3. Domenico Piccolo
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Corresponding author

Correspondence to Stefania Capecchi .

Editor information

Editors and Affiliations

  1. Department of Political Sciences, University of Naples Federico II, Napoli, Italy

    Francesco Palumbo

  2. Department of Statistical Sciences Paolo Fortunati, Alma Mater Studiorum, University of Bologna, Bologna, Italy

    Angela Montanari

  3. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maurizio Vichi

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Capecchi, S., Simone, R., Piccolo, D. (2017). An Inflated Model to Account for Large Heterogeneity in Ordinal Data. In: Palumbo, F., Montanari, A., Vichi, M. (eds) Data Science . Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-55723-6_16

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