TY - JOUR
T1 - Composite partial likelihood estimation for length-biased and right-censored data with competing risks
AU - Zhang, Feipeng
AU - Peng, Heng
AU - Zhou, Yong
N1 - Funding Information:
The authors are grateful to the Editor, an Associate Editor, and an anonymous reviewer for their insightful comments and constructive suggestions that lead to significant improvement in the revised manuscript. Zhang’s work is partially supported by National Natural Science Foundation of China (NSFC) (No. 11401194 ), the Fundamental Research Funds for the Central Universities (No. 531107050739 ). Peng’s research was supported in part by CERG grants by the Research Grants Council of Hong Kong (Nos. HKBU 202012 and HKBU 12302615 ), FRG grants from Hong Kong Baptist University (Nos. FRG2/12-13/077 and FRG2/14-15/064 ) and NSF of CHINA Grant (No. 10871054 ). Zhou’s work was supported by National Natural Science Foundation of China (NSFC) ( 71271128 ), the State Key Program of National Natural Science Foundation of China ( 71331006 and 91546202 ), NCMIS, Key Laboratory of RCSDS, AMSS, CAS ( 2008DP173182 ) and Shanghai First-class Discipline A, Program for Changjiang Scholars (PCSIRT) and Innovative Research Team in Shanghai University of Finance and Economics ( SUFEIRT13077 ).
PY - 2016/7
Y1 - 2016/7
N2 - This paper considers a competing risks model for survival data from length-biased sampling, where the survival times are left truncated by uniformly distributed random truncation times. We propose a composite partial likelihood estimating procedure for cause-specific failure probabilities using competing risks data. We establish the asymptotic properties of the proposed estimators, and present predictions of the cumulative incidence functions. Furthermore, we show how to construct simultaneous confidence bands for the cause-specific cumulative incidence functions for subjects with given risk factors. A simulation study demonstrates that the proposed estimators have good finite-sample performance. A real data example illustrates the method and the theory.
AB - This paper considers a competing risks model for survival data from length-biased sampling, where the survival times are left truncated by uniformly distributed random truncation times. We propose a composite partial likelihood estimating procedure for cause-specific failure probabilities using competing risks data. We establish the asymptotic properties of the proposed estimators, and present predictions of the cumulative incidence functions. Furthermore, we show how to construct simultaneous confidence bands for the cause-specific cumulative incidence functions for subjects with given risk factors. A simulation study demonstrates that the proposed estimators have good finite-sample performance. A real data example illustrates the method and the theory.
KW - Competing risks
KW - Composite partial likelihood
KW - Cumulative incidence function
KW - Length-biased and right censored data
KW - Resampling
UR - http://www.scopus.com/inward/record.url?scp=84965057151&partnerID=8YFLogxK
U2 - 10.1016/j.jmva.2016.04.002
DO - 10.1016/j.jmva.2016.04.002
M3 - Journal article
AN - SCOPUS:84965057151
SN - 0047-259X
VL - 149
SP - 160
EP - 176
JO - Journal of Multivariate Analysis
JF - Journal of Multivariate Analysis
ER -