期刊
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷 87, 期 4, 页码 631-639出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949655.2016.1222530
关键词
Competing risk; cumulative incidence function; GEE; interval censored data; missingcause of failure; multiple imputation
资金
- National Research Foundation of Korea [2014R1A2A2A01003567] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Competing risks often occur when subjects may fail from one of several mutually exclusive causes. For example, when a patient suffering a cancer may die from other cause, we are interested in the effect of a certain covariate on the probability of dying of cancer at a certain time. Several approaches have been suggested to analyse competing risk data in the presence of complete information of failure cause. In this paper, our interest is to consider the occurrence of missing causes as well as interval censored failure time. There exist no method to discuss this problem. We applied a Klein-Andersen's pseudo-value approach [Klein, JP Andersen PK. Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function. Biometrics. 2005;61:223-229] based on the estimated cumulative incidence function and a regression coefficient is estimated through a multiple imputation. We evaluate the suggested method by comparing with a complete case analysis in several simulation settings.
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