Kaplan-Meier estimator under association

JOURNAL OF MULTIVARIATE ANALYSIS

卷:67

Article

Cai, ZW ; Roussas, GG

关键词: censored data;    Kaplan-Meier estimator;    negative association;    positive association;    strong consistency;    variance estimator;    weak convergence;   

DOI  :  10.1006/jmva.1998.1769

来源: Elsevier

【 摘 要 】

Consider a long term study, where a series of possibly censored failure times is observed. Suppose the failure times have a common marginal distribution function F, but they exhibit a mode of dependence characterized by positive or negative association. Under suitable regularity conditions, it is shown that the Kaplan-Meier estimator (F) over tilde(n) of F is uniformly strongly consistent; rates for the convergence are also provided. Similar results are established for the empirical cumulative hazard rate function involved. Furthermore, a stochastic process generated by (F) over tilde(n) is shown to be weakly convergent to an appropriate Gaussian process. Finally, an estimator of the limiting variance of the Kaplan-Meier estimator is proposed and it is shown to be weakly convergent. (C) 1998 Academic Press.

【 授权许可】

Free