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ABSTRACT
The case-cohort design brings cost reduction in large cohort studies. In this paper, we consider a nonlinear quantile regression model for censored competing risks under the case-cohort design. Two different estimation equations are constructed with or without the covariates information of other risks included, respectively. The large sample properties of the estimators are obtained. The asymptotic covariances are estimated by using a fast resampling method, which is useful to consider further inferences. The finite sample performance of the proposed estimators is assessed by simulation studies. Also a real example is used to demonstrate the application of the proposed methods.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
Fan's work is partially sponsored by the National Natural Science Foundation of Tianyuan [11626155], Shanghai Pujiang Program [16PJC041]. Ma's research is partially supported by National Institutes of Health [grant R01 HL113548]. Zhou's work is supported by the State Key Program of National Natural Science Foundation of China [71331006], the State Key Program in the Major Research Plan of National Natural Science Foundation of China [91546202], National Center for Mathematics and Interdisciplinary Sciences (NCMIS), Key Laboratory of RCSDS, AMSS, CAS [2008DP173182] and Innovative Research Team of Shanghai University of Finance and Economics [IRTSHUFE13122402].