Journal article
Smoothed quantile regression for censored residual life
Computational statistics, Vol.38(2), pp.1001-1022
06/2023
DOI: 10.1007/s00180-022-01262-z
Abstract
We consider a regression modeling of the quantiles of residual life, remaining lifetime at a specific time. We propose a smoothed induced version of the existing non-smooth estimating equations approaches for estimating regression parameters. The proposed estimating equations are smooth in regression parameters, so solutions can be readily obtained via standard numerical algorithms. Moreover, the smoothness in the proposed estimating equations enables one to obtain a robust sandwich-type covariance estimator of regression estimators aided by an efficient resampling method. To handle data subject to right censoring, the inverse probability of censoring distribution is used as a weight. The consistency and asymptotic normality of the proposed estimator are established. Extensive simulation studies are conducted to validate the proposed estimator's performance in various finite samples settings. We apply the proposed method to dental study data evaluating the longevity of dental restorations.
Details
- Title: Subtitle
- Smoothed quantile regression for censored residual life
- Creators
- Kyu Hyun Kim - Yonsei UniversityDaniel J. Caplan - Univ Iowa, Coll Dent, Dept Prevent & Community Dent, Iowa City, IA USASangwook Kang - Yonsei University
- Resource Type
- Journal article
- Publication Details
- Computational statistics, Vol.38(2), pp.1001-1022
- Publisher
- Springer Nature
- DOI
- 10.1007/s00180-022-01262-z
- ISSN
- 0943-4062
- eISSN
- 1613-9658
- Number of pages
- 22
- Grant note
- 2020R1A2C1A0101313911 / National Research Foundation of Korea (NRF) - Korea government(MSIT); National Research Foundation of Korea; Ministry of Science, ICT & Future Planning, Republic of Korea; Ministry of Science & ICT (MSIT), Republic of Korea
- Language
- English
- Electronic publication date
- 07/30/2022
- Date published
- 06/2023
- Academic Unit
- Preventive and Community Dentistry
- Record Identifier
- 9984367586202771
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