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Lifetime Data Analysis

, Volume 15, Issue 3, pp 295–315 | Cite as

About an adaptively weighted Kaplan-Meier estimate

  • Jean-François Plante
Article

Abstract

The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier estimate. The proposed estimate is smoother than the usual Kaplan-Meier estimate and converges uniformly in probability to the target distribution. Simulations show that the performances of the weighted Kaplan-Meier estimate on finite samples exceed that of the usual Kaplan-Meier estimate. A case study is also presented.

Keywords

Adaptive weights Borrowing strength Kaplan-Meier estimate Nonparametrics Survival analysis Weighted inference 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Service d’enseignement des méthodes quantitatives de gestionHEC MontréalMontréalCanada

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