In this paper we introduce a Bayesian semiparametric model for bivariate and multivariate survival data. The marginal densities are well-known nonparametric survival models and the joint density is constructed via a mixture. Our construction also defines a copula and the properties of this new copula are studied. We also consider the model in the presence of covariates and, in particular, we find a simple generalisation of the widely used frailty model, which is based on a new bivariate gamma distribution
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-...
The aim of this paper is to explore multivariate survival techniques for the analysis of bivariate r...
The aim of this paper is to explore multivariate survival techniques for the analysis of bivariate r...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics and ...
A Bivariate survival model is constructed.This model is based on a frailty model that acts multiplic...
The frailty models are used to model the possible associations between survival times. Another alter...
In multivariate survival analyses, understanding and quantifying the association between survival ti...
For certain life cycle events a non-susceptible fraction of subjects will never undergo the event. I...
Multivariate survival data arise when each study subject may experience multiple events or when the ...
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-...
The aim of this paper is to explore multivariate survival techniques for the analysis of bivariate r...
The aim of this paper is to explore multivariate survival techniques for the analysis of bivariate r...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Our research focuses on exploring and developing flexible Bayesian methodologies to model both univa...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics and ...
A Bivariate survival model is constructed.This model is based on a frailty model that acts multiplic...
The frailty models are used to model the possible associations between survival times. Another alter...
In multivariate survival analyses, understanding and quantifying the association between survival ti...
For certain life cycle events a non-susceptible fraction of subjects will never undergo the event. I...
Multivariate survival data arise when each study subject may experience multiple events or when the ...
For multivariate failure time data, we propose a new class of shared gamma frailty models by imposin...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...