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Detecting latent components in ordinal data with overdispersion by means of a mixture distribution

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Abstract

The paper describes a mixture distribution generated by Beta Binomial and Uniform random variables to allow for a possible overdispersion in surveys when the response of interest is an ordinal variable. This approach considers the joint presence of feeling, uncertainty and a possible dispersion sometimes present in the evaluation contexts. After a discussion of the main properties of this class of models, asymptotic likelihood methods have been applied for efficient statistical inference. The implementation on the survey on household income and wealth (SHIW) will confirm the versatility of this distribution and the usefulness to distinguish the determinants of uncertainty and overdispersion in real data.

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Acknowledgments

The author thanks the Editor and the referees for suggestions which improved the paper. This research has been supported by Programme STAR (CUP E68C13000020003) at University of Naples Federico II and FIRB 2012 project (code RBFR12SHVV) at University of Perugia.

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

    Maria Iannario

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  1. Maria Iannario
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Correspondence to Maria Iannario.

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Iannario, M. Detecting latent components in ordinal data with overdispersion by means of a mixture distribution. Qual Quant 49, 977–987 (2015). https://doi.org/10.1007/s11135-014-0113-9

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  • DOI: https://doi.org/10.1007/s11135-014-0113-9

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