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http://dx.doi.org/10.5351/KJAS.2010.23.5.871

Analysis of Tumorigenicity Data with Informative Censoring  

Kim, Jin-Heum (Department of Applied Statistics, University of Suwon)
Kim, Youn-Nam (Graduate School of Public Health, Yonsei University)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.5, 2010 , pp. 871-882 More about this Journal
Abstract
In animal tumorigenicity data, the occurrence time of tumor is not observed because the existence of a tumor is examined only at either time of natural death or time of sacrifice for the animal. A three-state model (Health-Tumor onset-Death) is widely used to model the incomplete data. In this paper, we employed a frailty effect into the three-state model to incorporate the dependency of death on tumor occurrence when the time of natural death works as an informative censoring against the tumor onset time. For the inference of parameters, then the EM algorithm is considered in order to deal with missing quantities of tumor onset time and random frailty. The proposed method is applied to the bladder tumor data taken from Lindsey and Ryan (1993, 1994) and a simulation study is performed to show the behavior of the proposed estimators.
Keywords
Bladder cancer data; EM algorithm; gamma frailty effect; Gauss-Laguerre method; three-state model; tumorigenicity experiment;
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