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Maximum likelihood estimation for survey data with informative interval censoring

Author

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  • Angel G. Angelov

    (Umeå University)

  • Magnus Ekström

    (Umeå University)

Abstract

Interval-censored data may arise in questionnaire surveys when, instead of being asked to provide an exact value, respondents are free to answer with any interval without having pre-specified ranges. In this context, the assumption of noninformative censoring is violated, and thus, the standard methods for interval-censored data are not appropriate. This paper explores two schemes for data collection and deals with the problem of estimation of the underlying distribution function, assuming that it belongs to a parametric family. The consistency and asymptotic normality of a proposed maximum likelihood estimator are proven. A bootstrap procedure that can be used for constructing confidence intervals is considered, and its asymptotic validity is shown. A simulation study investigates the performance of the suggested methods.

Suggested Citation

  • Angel G. Angelov & Magnus Ekström, 2019. "Maximum likelihood estimation for survey data with informative interval censoring," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 217-236, June.
    • Handle: RePEc:spr:alstar:v:103:y:2019:i:2:d:10.1007_s10182-018-00329-x
    DOI: 10.1007/s10182-018-00329-x
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    References listed on IDEAS

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    Cited by:

    1. Fernando Rios-Avila & Gustavo Canavire-Bacarreza & Flavia Sacco-Capurro, 2024. "Recovering income distribution in the presence of interval-censored data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 22(4), pages 1039-1060, December.

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