Nonpararmetric estimation for interval censored competing risk data
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초록

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.

키워드

Competing risksinterval censored datainverse probability weightinglog rank testproduct limit estimator.
제목
Nonpararmetric estimation for interval censored competing risk data
저자
김양진권도영
DOI
10.7465/jkdi.2017.28.4.947
발행일
2017-07
저널명
한국데이터정보과학회지
28
4
페이지
947 ~ 955