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A method of correction for heaping error in the variables using validation data

Author

Listed:
  • Amar S. Ahmad

    (New York University)

  • Munther Al-Hassan

    (Dubai Men’s College)

  • Hamid Y. Hussain

    (Dubai Health Authority)

  • Nirmin F. Juber

    (New York University)

  • Fred N. Kiwanuka

    (Dubai Men’s College)

  • Mohammed Hag-Ali

    (Higher Colleges of Technology)

  • Raghib Ali

    (New York University)

Abstract

When self-reported data are used in statistical analysis to estimate the mean and variance, as well as the regression parameters, the estimates tend, in many cases, to be biased. This is because interviewees have a tendency to heap their answers to certain values. The aim of the paper is to examine the bias-inducing effect of the heaping error in self-reported data, and study the effect on the heaping error on the mean and variance of a distribution as well as the regression parameters. As a result a new method is introduced to correct the effects of bias due to the heaping error using validation data. Using publicly available data and simulation studies, it can be shown that the newly developed method is practical and can easily be applied to correct the bias in the estimated mean and variance, as well as in the estimated regression parameters computed from self-reported data. Hence, using the method of correction presented in this paper allows researchers to draw accurate conclusions leading to the right decisions, e.g. regarding health care planning and delivery.

Suggested Citation

  • Amar S. Ahmad & Munther Al-Hassan & Hamid Y. Hussain & Nirmin F. Juber & Fred N. Kiwanuka & Mohammed Hag-Ali & Raghib Ali, 2024. "A method of correction for heaping error in the variables using validation data," Statistical Papers, Springer, vol. 65(2), pages 687-704, April.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:2:d:10.1007_s00362-023-01405-4
    DOI: 10.1007/s00362-023-01405-4
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    References listed on IDEAS

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    1. Carlo G. Camarda & Paul H. C. Eilers & Jutta Gampe, 2017. "Modelling trends in digit preference patterns," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 893-918, November.
    2. Klerman, J.A., 1993. "Heaping in Retrospective Data: Insights from Malaysia Family Life Survey's Breastfeeding Data," Papers 93-21, RAND - Labor and Population Program.
    3. repec:plo:pone00:0214941 is not listed on IDEAS
    4. John Haaga, 1988. "Reliability of retrospective survey data on infant feeding," Demography, Springer;Population Association of America (PAA), vol. 25(2), pages 307-314, May.
    5. Torelli, Nicola & Trivellato, Ugo, 1993. "Modelling inaccuracies in job-search duration data," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 187-211, September.
    6. Fengyi Lin & Liming Guan & Wenchang Fang, 2011. "Heaping in Reported Earnings: Evidence from Monthly Financial Reports of Taiwanese Firms," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(2), pages 62-73, March.
    7. Thomas Augustin & Joachim Wolff, 2004. "A bias analysis of Weibull models under heaped data," Statistical Papers, Springer, vol. 45(2), pages 211-229, April.
    8. Alan I. Barreca & Melanie Guldi & Jason M. Lindo & Glen R. Waddell, 2011. "Saving Babies? Revisiting the effect of very low birth weight classification," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 2117-2123.
    Full references (including those not matched with items on IDEAS)

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