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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

Published in

AStA Advances in Statistical Analysis
2019, volume: 103, number: 2, pages: 217-236

SLU Authors

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

  • DOI: https://doi.org/10.1007/s10182-018-00329-x

Permanent link to this page (URI)

https://res.slu.se/id/publ/100476