Maximum likelihood estimation for survey data with informative interval censoring

Angel G. Angelov () and Magnus Ekström ()
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Angel G. Angelov: Umeå University
Magnus Ekström: Umeå University

AStA Advances in Statistical Analysis, 2019, vol. 103, issue 2, No 3, 217-236

Abstract: 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.

Keywords: Informative interval censoring; Maximum likelihood; Parametric estimation; Questionnaire surveys; Self-selected intervals (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10182-018-00329-x

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