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http://dx.doi.org/10.7465/jkdi.2017.28.4.947

Nonpararmetric estimation for interval censored competing risk data  

Kim, Yang-Jin (Department of Statistics, Sookmyung Women's University)
Kwon, Do young (Department of Statistics, Sookmyung Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.4, 2017 , pp. 947-955 More about this Journal
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;
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Times Cited By KSCI : 2  (Citation Analysis)
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