# MODELING HETEROGENEITY FOR BIVARIATE SURVIVAL DATA BY POWER VARIANCE FUNCTION DISTRIBUTION

@inproceedings{Hanagal2002MODELINGHF, title={MODELING HETEROGENEITY FOR BIVARIATE SURVIVAL DATA BY POWER VARIANCE FUNCTION DISTRIBUTION}, author={David D. Hanagal}, year={2002} }

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…

## 2 Citations

Joint modeling of bivariate longitudinal and survival data in spouse pairs

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We investigated the association between longitudinally measured depression scores and survival times simultaneously for paired spouse data from the Cardiovascular Health Study (CHS). We propose a…

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The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced and provides consistent estimators of the standard errors of the parameters' estimators.

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