Assume that (Xi, Yi), 1 <= i <= n, are independent (p + 1)-variate vectors, where each Yi is at risk of being censored from the right and Xi is a vector of observable covariables. We introduce a (p + 1)-dimensional extension of the Kaplan-Meier estimator and show its consistency. Also a general strong law for Kaplan-Meier integrals is proved, which, e.g., may be utilized to prove consistency of a new regression parameter estimator under random censorship.
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Volume (Year): 45 (1993) Issue (Month): 1 (April) Pages: 89-103 Download reference. The following formats are available: HTML
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