We generalize the previously developed Non-PH CTDL-Gamma and the PH Weibull-Gamma frailty models to correlated survival data. In particular, we seek analytical results using the marginal approach, to determine whether the univariate results generalize to the multivariate context. We consider both the shared and correlated frailty cases.We also develop non-parametric frailty models which enable us to check the appropriateness of the assumed distributional form of the random effect
Non-PH parametric survival modelling is developed within the framework of the mul tiple logistic fun...
A new class of bivariate survival distributions is constructed from a given family of survival distr...
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...
peer-reviewedWe generalize the previously developed Non-PH CTDL-Gamma and the PH Weibull-Gamma frai...
Correlated survival times may be modelled by introducing a random effect, or frailty, component into...
peer-reviewedIn the survival analysis literature, the standard model for data analysis is the semi-...
Correlated survival times can be modelled by introducing a random effect, or frailty component, into...
peer-reviewedCorrelated survival times may be modelled by introducing a random effect, or frailty, ...
Frequently in the analysis of survival data, survival times within the same group are correlated due...
Non-PH parametric survival modelling is developed within the frame- work of the multiple logistic fu...
The aim of this paper is to present an overview of the methods used in modeling survival data. Since...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
A key assumption of the popular Cox model is that the observations in the study are statistically in...
Frailty models are the survival data analog to regression models, which account for heterogeneity an...
Non-PH parametric survival modelling is developed within the framework of the mul tiple logistic fun...
A new class of bivariate survival distributions is constructed from a given family of survival distr...
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...
peer-reviewedWe generalize the previously developed Non-PH CTDL-Gamma and the PH Weibull-Gamma frai...
Correlated survival times may be modelled by introducing a random effect, or frailty, component into...
peer-reviewedIn the survival analysis literature, the standard model for data analysis is the semi-...
Correlated survival times can be modelled by introducing a random effect, or frailty component, into...
peer-reviewedCorrelated survival times may be modelled by introducing a random effect, or frailty, ...
Frequently in the analysis of survival data, survival times within the same group are correlated due...
Non-PH parametric survival modelling is developed within the frame- work of the multiple logistic fu...
The aim of this paper is to present an overview of the methods used in modeling survival data. Since...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
A key assumption of the popular Cox model is that the observations in the study are statistically in...
Frailty models are the survival data analog to regression models, which account for heterogeneity an...
Non-PH parametric survival modelling is developed within the framework of the mul tiple logistic fun...
A new class of bivariate survival distributions is constructed from a given family of survival distr...
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...