Quantile regression for competing risks data from stratified case-cohort studies: an induced-smoothing approach

DOI10.1080/00949655.2022.2134376OpenAlexW4307170017MaRDI QIDQ6050803

Unnamed Author, Sangwook Kang, Sangbum Choi

Publication date: 19 September 2023

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2022.2134376

zbMATH Keywords

resamplingsurvival analysiscumulative incidence functionweighted estimating equationscohort samplinginverse probability weight

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Fast accelerated failure time modeling for case-cohort data
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• Competing Risks
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• Calibration Regression of Censored Lifetime Medical Cost
• A Proportional Hazards Model for the Subdistribution of a Competing Risk
• Additive hazards regression for case-cohort studies
• Quantile regression for competing risks analysis under case-cohort design
• Smoothed quantile regression analysis of competing risks
• Locally Weighted Censored Quantile Regression
• Standard errors and covariance matrices for smoothed rank estimators
• Semiparametric Accelerated Failure Time Modeling for Clustered Failure Times From Stratified Sampling
• More efficient estimators for case-cohort studies
• Improving the Efficiency of Relative-Risk Estimation in Case-Cohort Studies

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