Modeling Heterogeneity for Bivariate Survival Data by Power Variance Function Distribution
نویسنده
چکیده
We propose a bivariate Weibull regression model with frailty which is generated by power variance function distribution. We assume that the bivariate survival data follow bivariate Weibull of Hanagal (2005a) and distribution of censoring variable is independent of the two life times. There are some interesting situations like survival times in genetic epidemiology, survival times of dental implants of patients and survival times of twin births (both monozygotic and dizygotic) where genetic behavior (which is unknown and random) of patients follows a power variance function frailty distribution. These are the situations which motivate to study this particular model. We propose two stage maximum likelihood estimation procedure for the parameters and develop large sample tests for no frailty and the significance of regression parameters in the proposed model.
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