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Modelling cognitive response patterns to survey questions using the class of CUB models

Author

Listed:
  • Stefania Capecchi

    (University of Naples Federico II)

  • Romina Gambacorta

    (Bank of Italy)

  • Rosaria Simone

    (University of Naples Federico II)

  • Domenico Piccolo

    (University of Naples Federico II)

Abstract

Responses to questionnaire items can be influenced by various factors including sample design, interview mode and/or how questions are phrased. To analyse these aspects, this paper draws on the Bank of Italy's surveys of households and firms, which employ different survey modes or questions with different phrasings, response options, or graphical features for sub-samples of respondents. We exploit the potential of CUB (Combination of Uniform Discrete and shifted Binomial random variables) modelling for the analysis of ordinal data. CUB models are able to capture and identify the different components of the cognitive process behind the responses and to study how these are related to the relevant covariates (such as respondents' characteristics). The results show that in general, although diverse survey modes and a different phrasing or graphical representation of questions may yield somewhat different findings in terms of uncertainty, responses to relevant questions such as those on reported satisfaction or expectations did not produce pronounced differences in data reliability.

Suggested Citation

  • 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.
    • Handle: RePEc:bdi:opques:qef_885_24
    as

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    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2024-0885/QEF_885_24.pdf
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    References listed on IDEAS

    as
    1. Ivan Faiella & Romina Gambacorta, 2007. "The Weighting Process in the SHIW," Temi di discussione (Economic working papers) 636, Bank of Italy, Economic Research and International Relations Area.
    2. 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.
    3. Annette Jäckle & Caroline Roberts & Peter Lynn, 2010. "Assessing the Effect of Data Collection Mode on Measurement," International Statistical Review, International Statistical Institute, vol. 78(1), pages 3-20, April.
    4. Romina Gambacorta & Martina Lo Conte & Manuela Murgia & Andrea Neri & Roberta Rizzi & Francesca Zanichelli, 2018. "Mind the mode: lessons from a web survey on household finances," Questioni di Economia e Finanza (Occasional Papers) 437, Bank of Italy, Economic Research and International Relations Area.
    5. 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.
    6. Giovanni Cerulli & Rosaria Simone & Francesca Di Iorio & Domenico Piccolo & Christopher F Baum, 2022. "Fitting mixture models for feeling and uncertainty for rating data analysis," Stata Journal, StataCorp LP, vol. 22(1), pages 195-223, March.
    7. 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.
    8. Braunsberger, Karin & Wybenga, Hans & Gates, Roger, 2007. "A comparison of reliability between telephone and web-based surveys," Journal of Business Research, Elsevier, vol. 60(7), pages 758-764, July.
    9. Anna DeCastellarnau, 2018. "A classification of response scale characteristics that affect data quality: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1523-1559, July.
    10. 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.
    11. Domenico Piccolo & Rosaria Simone, 2019. "Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 477-493, September.
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    More about this item

    Keywords

    survey mode; CUB models; data quality; questionnaire design;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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