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Research article - Peer-reviewed, 2022

Quantile regression with interval-censored data in questionnaire-based studies

Angelov, Angel G.; Ekstrom, Magnus; Puzon, Klarizze; Arcenas, Agustin; Kristrom, Bengt


Interval-censored data can arise in questionnaire-based studies when the respondent gives an answer in the form of an interval without having pre-specified ranges. Such data are called self-selected interval data. In this case, the assumption of independent censoring is not fulfilled, and therefore the ordinary methods for interval-censored data are not suitable. This paper explores a quantile regression model for self-selected interval data and suggests an estimator based on estimating equations. The consistency of the estimator is shown. Bootstrap procedures for constructing confidence intervals are considered. A simulation study indicates satisfactory performance of the proposed methods. An application to data concerning price estimates is presented.


Interval-censored data; Dependent censoring; Self-selected interval; Quantile regression; Estimating equation

Published in

Computational Statistics

Authors' information

Angelov, Angel G.
Umea University
Angelov, Angel G.
University of Sofia
Umeå University
Swedish University of Agricultural Sciences, Department of Forest Resource Management
Arcenas, Agustin
University of the Philippines Diliman
Swedish University of Agricultural Sciences, Department of Forest Economics
Puzon, Klarizze
United Nations University World Institute for Development Economics Research

UKÄ Subject classification

Probability Theory and Statistics

Publication Identifiers


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