Assessing cumulative incidence functions under the semiparametric additive risk model.
In analyzing competing risks data, a quantity of considerable interest is the cumulative incidence function. Often, the effect of covariates on the cumulative incidence function is modeled via the proportional hazards model for the cause-specific hazard function. As the proportionality assumption may be too restrictive in practice, we consider an alternative more flexible semiparametric additive hazards model of (Biometrika 1994; 81:501-514) for the cause-specific hazard. This model specifies the effect of covariates on the cause-specific hazard to be additive as well as allows the effect of some covariates to be fixed and that of others to be time varying. We present an approach for constructing confidence intervals as well as confidence bands for the cause-specific cumulative incidence function of subjects with given values of the covariates. Furthermore, we also present an approach for constructing confidence intervals and confidence bands for comparing two cumulative incidence functions given values of the covariates. The finite sample property of the proposed estimators is investigated through simulations. We conclude our paper with an analysis of the well-known malignant melanoma data using our method.
Hyun
Seunggeun
S
Division of Mathematics and Computer Science, University of South Carolina Upstate, Spartanburg, SC 29303, USA.
Sun
Yanqing
Y
Sundaram
Rajeshwari
R
D000328:Adult; D000368:Aged; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D008297:Male; D008545:Melanoma / Q000473:pathology; D008875:Middle Aged; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000706:statistics & numerical data; D016019:Survival Analysis