Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Regularized linear censored quantile regressionRegularized linear censored quantile regression

Other Titles
Regularized linear censored quantile regression
Authors
Son, MinjeongChoi, TaehwaShin, Seung JunJung, YoonsuhChoi, Sangbum
Issue Date
6월-2022
Publisher
SPRINGER HEIDELBERG
Keywords
Accelerated failure time model; Kernel smoothing; Martingale; Sufficient dimension reduction; Survival analysis; Variable selection
Citation
JOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.51, no.2, pp.589 - 607
Indexed
SCIE
SCOPUS
KCI
OTHER
Journal Title
JOURNAL OF THE KOREAN STATISTICAL SOCIETY
Volume
51
Number
2
Start Page
589
End Page
607
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/138500
DOI
10.1007/s42952-021-00155-z
ISSN
1226-3192
Abstract
For right-censored survival data, censored quantile regression is emerging as an attractive alternative to the Cox's proportional hazards and the accelerated failure time models. Censored quantile regression has been considered as a robust and flexible alternative in the sense that it can capture a variety of treatment effects at different quantile levels of survival function. In this paper, we present a novel regularized estimation and variable selection procedure for censored quantile regression model. Statistical inference on censored quantile regression is often based on a martingale-based estimating function that may require a strict linearity assumption and a grid-search procedure. Instead, we employ a local kernel-based Kaplan-Meier estimator and modify the quantile loss function to facilitate censored observations. This approach allows us to assume the linearity condition only at the particular quantile level of interest. Our proposed method is then regularized by using LASSO and adaptive LASSO, along with sufficient dimension reduction, to select a subset of informative covariates in a high-dimension setting. The asymptotic properties of the proposed estimators are rigorously studied. Their finite-sample properties and practical utility are explored via simulation studies and application to PBC data.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Political Science & Economics > Department of Statistics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE