Ying, Z.; Wei, L. J. The Kaplan-Meier estimate for dependent failure time observations. (English) Zbl 0798.62048 J. Multivariate Anal. 50, No. 1, 17-29 (1994). Summary: In some long term medical follow-up studies, a series of dependent and possibly censored failure times may be observed. Suppose that these failure times were generated from the same distribution function, and inferences about it are of our main interest.We show that under rather weak conditions for the dependence among the observations, the Kaplan-Meier estimator is still consistent and asymptotically normal. For a special dependent case in which highly stratified data are observed, a valid estimate for the limiting variance of the Kaplan-Meier estimate is also provided. Our proposal is illustrated with an example. Cited in 31 Documents MSC: 62G05 Nonparametric estimation 62G20 Asymptotic properties of nonparametric inference 62P10 Applications of statistics to biology and medical sciences; meta analysis Keywords:phi-mixing; consistency; asymptotic normality; weak convergence; long term medical follow-up studies; censored failure times; dependence; Kaplan-Meier estimator; highly stratified data; limiting variance PDFBibTeX XMLCite \textit{Z. Ying} and \textit{L. J. Wei}, J. Multivariate Anal. 50, No. 1, 17--29 (1994; Zbl 0798.62048) Full Text: DOI