B0308
Title: Copula based dependent censoring in cure models
Authors: Morine Delhelle - UCLouvain (Belgium) [presenting]
Ingrid Van Keilegom - KU Leuven (Belgium)
Abstract: In survival data analysis datasets with both a cure fraction (individuals who will never experience the event of interest) and dependent censoring (loss of follow-up for a reason linked to the event of interest before the occurrence of this event) are not scarce and are important to use an adequate model dealing with these two characteristics of bias should be avoided in parameters estimations or false conclusions in clinical trials. A fully parametric survival mixture cure model is proposed that takes possible dependent censoring into account which is based on an unknown copula that describes the relation between the survival and censoring times. So, the advantages of the model are that dependent censoring and the cure fraction are both considered and that the copula is not assumed to be known. Moreover, it allows the estimation of the strength of dependence. The situations with and without covariates will be discussed.
