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Nonpararmetric estimation for interval censored competing risk data
Journal of the Korean Data & Information Science Society 2017;28:947-55
Published online July 31, 2017
© 2017 Korean Data & Information Science Society.

Yang-Jin Kim1 · Do young Kwon2

12Department of Statistics, Sookmyung Women's University
Correspondence to: Yang-Jin Kim
Associate Professor, Department of Statistics, Sookmyung Women's University, Seoul 04310, Korea, E-mail: yjin@sookmyung.ac.kr
Received July 9, 2017; Revised July 24, 2017; Accepted July 26, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
A competing risk analysis has been applied when subjects experience more than one type of end points. Geskus (2011) showed three types of estimators of CIF are equivalent under left truncated and right censored data. We extend his approach to an interval censored competing risk data by using a modified risk set and evaluate their performance under several sample sizes. These estimators show very similar results. We also suggest a test statistic combining Sun's test for interval censored data and Gray's test for right censored data. The test sizes and powers are compared under several cases. As a real data application, the suggested method is applied a data where the feasibility of the vaccine to HIV was assessed in the injecting drug uses.
Keywords : Competing risks, interval censored data, inverse probability weighting, log rank test, product limit estimator