Case-cohort studies for clustered failure time data with a cure fraction

In epidemiological studies, the case-cohort design is a widely used method for their outstanding cost-effectiveness. Most of the existing works for the case-cohort design are focused on univariate failure time data. However, clustered failure time data are commonly encountered in epidemiological studies. In this article, we study the marginal nonmixture cure model for clustered failure time data with a cure fraction in the context of case-cohort design. A sieve semiparametric likelihood method is proposed to estimate the parametric and nonparametric components. The proposed method is easy to implement. The resulting estimators are shown to be strongly consistent and asymptotically normal. Simulation studies are carried out to assess the finite sample performance of the proposed method. We also analyze a real dataset from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial to illustrate our method.