Composite quantile regression analysis of survival data with missing cause-of-failure information and its application to breast cancer clinical trial

DOI10.1016/j.csda.2023.107711MaRDI QIDQ6168918

Chengxin Wu, Yu-Ye Zou

Publication date: 11 July 2023

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

missing at randomvariable selectioncomposite quantile regressionsingle-index coefficient modelcause-of-failure information

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Composite quantile regression and variable selection in single-index coefficient model
• Variable selection for single-index varying-coefficient model
• Variable selection and coefficient estimation via composite quantile regression with randomly censored data
• The weighted least square based estimators with censoring indicators missing at random
• Linear regression analysis of survival data with missing censoring indicators
• Statistical inference for a single-index varying-coefficient model
• Profile empirical-likelihood inferences for the single-index-coefficient regression model
• Composite quantile regression and the oracle model selection theory
• Regression analysis with randomly right-censored data
• Quantile regression for partially linear varying-coefficient model with censoring indicators missing at random
• Limiting distributions for \(L_1\) regression estimators under general conditions
• Testing for the parametric parts in a single-index varying-coefficient model
• Quantile regression and variable selection for partially linear single-index models with missing censoring indicators
• Quantile regression and variable selection of partial linear single-index model
• New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
• Quantile regression for competing risks data with missing cause of failure
• Regression Quantiles
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
• Semiparametric Estimation of Index Coefficients
• On extended partially linear single-index models
• Weighted composite quantile regression with censoring indicators missing at random

This page was built for publication: Composite quantile regression analysis of survival data with missing cause-of-failure information and its application to breast cancer clinical trial