AbstractThe Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibly time-dependent fixed and random covariates. Stratified Cox, grouped data and Weibull models can be used. Random effects can be either log-gamma or normally distributed and can account for a pedigree structure. Variance parameters are estimated in a Bayesian context. It is possible to account for the correlated nature of two random effects either by specifying a known correlation coefficient or estimating it from the data. An R interface...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
Extensions in the field of joint modeling of correlated data and dynamic predictions improve the dev...
AbstractThe Survival Kit is a Fortran 90 Software intended for survival analysis using proportional ...
The use of frailty models to account for unobserved individual he terogeneity and other random effec...
Frailty models are very useful for analysing correlated survival data, when observations are cluster...
Correlated survival outcomes occur quite frequently in the biomedical research. Available software i...
Mots clefs: Statistic, Frailty models, clustered data, recurrent events Frailty models are extension...
When analyzing correlated time to event data, shared frailty (random effect) models are particularly...
A non-proportional hazards model is developed. The model can accommodate right censored, interval ce...
This paper introduces a novel model and software package for parametric survival modelling of indivi...
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods ...
Multivariate survival analysis involves the study of failure times, including the influence of covar...
AbstractA new class of bivariate survival distributions is constructed from a given family of surviv...
The study of events involving an element of time has a long and important history in statistical res...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
Extensions in the field of joint modeling of correlated data and dynamic predictions improve the dev...
AbstractThe Survival Kit is a Fortran 90 Software intended for survival analysis using proportional ...
The use of frailty models to account for unobserved individual he terogeneity and other random effec...
Frailty models are very useful for analysing correlated survival data, when observations are cluster...
Correlated survival outcomes occur quite frequently in the biomedical research. Available software i...
Mots clefs: Statistic, Frailty models, clustered data, recurrent events Frailty models are extension...
When analyzing correlated time to event data, shared frailty (random effect) models are particularly...
A non-proportional hazards model is developed. The model can accommodate right censored, interval ce...
This paper introduces a novel model and software package for parametric survival modelling of indivi...
Survival data analysis is a very broad field of statistics, encompassing a large variety of methods ...
Multivariate survival analysis involves the study of failure times, including the influence of covar...
AbstractA new class of bivariate survival distributions is constructed from a given family of surviv...
The study of events involving an element of time has a long and important history in statistical res...
This book provides a groundbreaking introduction to the likelihood inference for correlated survival...
The hazard function plays a central role in survival analysis. In a homogeneous population, the dist...
Extensions in the field of joint modeling of correlated data and dynamic predictions improve the dev...