The aim of this paper is to develop the three-State Illness-Death model taking into account the clustered nature of data. For this purpose, the Frailty Model has been applied in Multi-State framework, assuming that the underlying process is timehomogeneous Markovian. The unknown parameters of the model have been estimated both in presence of complete observations and in case of censoring. Thus, the impact and the effects of censoring on the estimation have been analyzed. The relevance of the proposed model is illustrated by means of a simulation study, in order to validate the model assumptions and the performance of the proposed estimators.
Illness-Death Model for Clustered Data
RESTAINO, MARIALUISA
2010-01-01
Abstract
The aim of this paper is to develop the three-State Illness-Death model taking into account the clustered nature of data. For this purpose, the Frailty Model has been applied in Multi-State framework, assuming that the underlying process is timehomogeneous Markovian. The unknown parameters of the model have been estimated both in presence of complete observations and in case of censoring. Thus, the impact and the effects of censoring on the estimation have been analyzed. The relevance of the proposed model is illustrated by means of a simulation study, in order to validate the model assumptions and the performance of the proposed estimators.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
