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Regression analysis of case K interval-censored failure time data in the presence of informative censoring.
Biometrics 2016; 72(4):1103-1112B

Abstract

Interval-censored failure time data occur in many fields such as demography, economics, medical research, and reliability and many inference procedures on them have been developed (Sun, 2006; Chen, Sun, and Peace, 2012). However, most of the existing approaches assume that the mechanism that yields interval censoring is independent of the failure time of interest and it is clear that this may not be true in practice (Zhang et al., 2007; Ma, Hu, and Sun, 2015). In this article, we consider regression analysis of case K interval-censored failure time data when the censoring mechanism may be related to the failure time of interest. For the problem, an estimated sieve maximum-likelihood approach is proposed for the data arising from the proportional hazards frailty model and for estimation, a two-step procedure is presented. In the addition, the asymptotic properties of the proposed estimators of regression parameters are established and an extensive simulation study suggests that the method works well. Finally, we apply the method to a set of real interval-censored data that motivated this study.

Authors+Show Affiliations

School of Mathematics, Jilin University, Changchun 130012, China.School of Mathematics and Statistics & Hubei Key Laboratory of Mathematical Sciences, Central China Normal University, Wuhan 430079, China.Department of Statistics, University of Missouri, Columbia, Missouri 65211, U.S.A.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

27123560

Citation

Wang, Peijie, et al. "Regression Analysis of Case K Interval-censored Failure Time Data in the Presence of Informative Censoring." Biometrics, vol. 72, no. 4, 2016, pp. 1103-1112.
Wang P, Zhao H, Sun J. Regression analysis of case K interval-censored failure time data in the presence of informative censoring. Biometrics. 2016;72(4):1103-1112.
Wang, P., Zhao, H., & Sun, J. (2016). Regression analysis of case K interval-censored failure time data in the presence of informative censoring. Biometrics, 72(4), pp. 1103-1112. doi:10.1111/biom.12527.
Wang P, Zhao H, Sun J. Regression Analysis of Case K Interval-censored Failure Time Data in the Presence of Informative Censoring. Biometrics. 2016;72(4):1103-1112. PubMed PMID: 27123560.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Regression analysis of case K interval-censored failure time data in the presence of informative censoring. AU - Wang,Peijie, AU - Zhao,Hui, AU - Sun,Jianguo, Y1 - 2016/04/28/ PY - 2015/07/01/received PY - 2016/03/01/revised PY - 2016/03/01/accepted PY - 2016/4/29/pubmed PY - 2017/9/26/medline PY - 2016/4/29/entrez KW - Case K interval-censored data KW - Informative censoring KW - Proportional hazards model KW - Sieve maximum-likelihood estimation SP - 1103 EP - 1112 JF - Biometrics JO - Biometrics VL - 72 IS - 4 N2 - Interval-censored failure time data occur in many fields such as demography, economics, medical research, and reliability and many inference procedures on them have been developed (Sun, 2006; Chen, Sun, and Peace, 2012). However, most of the existing approaches assume that the mechanism that yields interval censoring is independent of the failure time of interest and it is clear that this may not be true in practice (Zhang et al., 2007; Ma, Hu, and Sun, 2015). In this article, we consider regression analysis of case K interval-censored failure time data when the censoring mechanism may be related to the failure time of interest. For the problem, an estimated sieve maximum-likelihood approach is proposed for the data arising from the proportional hazards frailty model and for estimation, a two-step procedure is presented. In the addition, the asymptotic properties of the proposed estimators of regression parameters are established and an extensive simulation study suggests that the method works well. Finally, we apply the method to a set of real interval-censored data that motivated this study. SN - 1541-0420 UR - https://www.unboundmedicine.com/medline/citation/27123560/Regression_analysis_of_case_K_interval_censored_failure_time_data_in_the_presence_of_informative_censoring_ L2 - https://doi.org/10.1111/biom.12527 DB - PRIME DP - Unbound Medicine ER -