Bayesian inference for modelling the uncertainty by a mixture model for rating data

• Maria Iannario ; Claudia Tarantola ^[1]
  1. [1] University of Pavia

     University of Pavia

     Pavía, Italia

     
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 350-353
• Idioma: inglés
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• Resumen

  • In this paper we perform Bayesian quantitative analysis of the cup model, which is a two-component mixture model recently introduced for the analysis of ordinal data. It combines a standard cumulative model with a discrete Uniform distribution used to take into account the uncertainty in the rating process.

    Since the posterior distribution of the parameters of interest is not in a closed form, MCMC methods are used to simulate from it. The performance of the proposed methodology has been evaluated via real data o ering practical suggestions for using this approach in social-science, medicine or economic settings when an ordinal response is provided.