Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan–Meier estimator

Ross L. Prentice () and Shanshan Zhao ()
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Ross L. Prentice: Fred Hutchinson Cancer Research Center
Shanshan Zhao: National Institute of Environmental Health Sciences

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2018, vol. 24, issue 1, No 2, 3-27

Abstract: Abstract The Dabrowska (Ann Stat 16:1475–1489, 1988) product integral representation of the multivariate survivor function is extended, leading to a nonparametric survivor function estimator for an arbitrary number of failure time variates that has a simple recursive formula for its calculation. Empirical process methods are used to sketch proofs for this estimator’s strong consistency and weak convergence properties. Summary measures of pairwise and higher-order dependencies are also defined and nonparametrically estimated. Simulation evaluation is given for the special case of three failure time variates.

Keywords: Censoring; Dabrowska estimator; Failure times; Kaplan–Meier estimator; Multivariate; Nonparametric; Product integral; Survivor function; Trivariate dependency (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10985-016-9383-y

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