Some simulation results under random censorship models

by Gerhard Dikta, Rolf Hansmann, and Christian Schmidt .

Abstract: We consider the Kaplan-Meier and a new semiparametric approach to estimate the distribution function in the random censorship model. Corresponding estimators of several functionals are compared by Monte Carlo under heavy censoring. Furthermore, some simulation results are included to illustrate the influence of linear dependence between lifetime and censoring time on the different approaches.

Key Words: Censored data, maximum likelihood estimation, Kaplan-Meier estimator, proportional hazards model

Authors:
Gerhard Dikta, dikta@fh-aachen.de
Rolf Hansmann, hansmann@ibs-logistik.de
Christian Schmidt, schmidt@fh-aachen.de

Editor: Jugal K. Ghorai, jugal@csd.uwm.edu

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