Weighted composite quantile regression with censoring indicators missing at random

DOI10.1080/03610926.2019.1678638OpenAlexW2980630553MaRDI QIDQ5079994

Fang-Yin Xu, Wu-Xin Fu, Weijun Jiang, Jiang-Feng Wang

Publication date: 30 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1678638

zbMATH Keywords

asymptotic normalitymissing at randomvariable selectioncomposite quantile regressioncensoring indicator

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Statistics (62-XX) Estimation in survival analysis and censored data (62N02)

Related Items (5)

Composite quantile regression for heteroscedastic partially linear varying-coefficient models with missing censoring indicators ⋮ Partially functional linear quantile regression model and variable selection with censoring indicators MAR ⋮ Composite quantile regression analysis of survival data with missing cause-of-failure information and its application to breast cancer clinical trial ⋮ Survival prediction model for right-censored data based on improved composite quantile regression neural network ⋮ Statistical inference for the heteroscedastic partially linear varying-coefficient errors-in-variables model with missing censoring indicators

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