Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan-Meier estimator.
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.
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. rprentic@fhcrc.org.
Ross L
RL
Prentice
National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA.
Shanshan
S
Zhao
D003198:Computer Simulation; D006801:Humans; D053208:Kaplan-Meier Estimate; D015999:Multivariate Analysis; D018709:Statistics, Nonparametric; D016019:Survival Analysis
Censoring; Dabrowska estimator; Failure times; Kaplan–Meier estimator; Multivariate; Nonparametric; Product integral; Survivor function; Trivariate dependency
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