A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data
Article first published online: 9 MAY 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 16, pages 1933–1951, 20 July 2011
How to Cite
Zhang,, X., Zhang, M.-J. and Fine, J. (2011), A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data. Statist. Med., 30: 1933–1951. doi: 10.1002/sim.4264
- Issue published online: 15 JUN 2011
- Article first published online: 9 MAY 2011
- Manuscript Accepted: 21 MAR 2011
- Manuscript Received: 10 NOV 2009
- competing risks;
- cumulative incidence function;
- proportional hazards model;
With competing risks failure time data, one often needs to assess the covariate effects on the cumulative incidence probabilities. Fine and Gray proposed a proportional hazards regression model to directly model the subdistribution of a competing risk. They developed the estimating procedure for right-censored competing risks data, based on the inverse probability of censoring weighting. Right-censored and left-truncated competing risks data sometimes occur in biomedical researches. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with right-censored and left-truncated data. We adopt a new weighting technique to estimate the parameters in this model. We have derived the large sample properties of the proposed estimators. To illustrate the application of the new method, we analyze the failure time data for children with acute leukemia. In this example, the failure times for children who had bone marrow transplants were left truncated. Copyright © 2011 John Wiley & Sons, Ltd.