The aim of this paper is to present an overview of the methods used in modeling survival data. Since the topic of my future Ph.D. thesis is Statistical models for correlated survival data we introduce the use of frailties as an equivalent of random effects in common statistical modeling together with its connection to correlation. Frailty model, how model with frailties is called, uses frailties as a parameter for individuals. Those who are most frail will experience an event earlier than others
In survival analysis recurrent event times are often observed on the same subject. These event times...
The inclusion of latent frailties in survival models can serve two purposes: (1) the modelling of de...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
This book presents the basic concepts of survival analysis and frailty models, covering both fundame...
The concept of frailty offers a convenient way to introduce unobserved heterogeneity and association...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
This thesis deals with frailty modelling, a framework devised to analyse clustered survival data. Th...
The emphasis of this thesis lies on complex survival data and on the modelling of this kind of data....
Frailty models are the survival data analog to regression models, which account for heterogeneity an...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
About this book Introduces Frailty Models from a basic level that is missing in other books, making...
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods ...
Dependent survival data arise in many contexts. One context is clustered survival data, where surviv...
Synopsis. In this paper we discuss the notion of individual frailty and its interpretation. In addit...
Frailty models are useful for handling dependence in multivariate times to events data, where the de...
In survival analysis recurrent event times are often observed on the same subject. These event times...
The inclusion of latent frailties in survival models can serve two purposes: (1) the modelling of de...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
This book presents the basic concepts of survival analysis and frailty models, covering both fundame...
The concept of frailty offers a convenient way to introduce unobserved heterogeneity and association...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
This thesis deals with frailty modelling, a framework devised to analyse clustered survival data. Th...
The emphasis of this thesis lies on complex survival data and on the modelling of this kind of data....
Frailty models are the survival data analog to regression models, which account for heterogeneity an...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
About this book Introduces Frailty Models from a basic level that is missing in other books, making...
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods ...
Dependent survival data arise in many contexts. One context is clustered survival data, where surviv...
Synopsis. In this paper we discuss the notion of individual frailty and its interpretation. In addit...
Frailty models are useful for handling dependence in multivariate times to events data, where the de...
In survival analysis recurrent event times are often observed on the same subject. These event times...
The inclusion of latent frailties in survival models can serve two purposes: (1) the modelling of de...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...