… , also called frailty, is a major concern in the application of survival analysis. Hazard rates do
… , but are strongly influenced by selection effects operating in the population. The individuals …

… survival data and association in multivariate survival can both be modelled by the inclusion
of frailty effects… This paper investigates the consequences of ignoring frailty in analysis, fitting …

… A frailty model is a random effects model for time variables, where the random effect (the
frailty) has a multiplicative effect on … times given the frailty. This approach can be used both for …

… This study aims to analyze the impact of frailty, multimorbidity and disability on the survival
of … It is a longitudinal study, with 133 elderly people initially evaluated in relation to frailty, …

… We concentrate on the use of frailty models in survival analysis. … In section 3, we analyze
the effect of unobserved heterogeneity in shared frailty models, covering clustered survival data, …

… The frailty model for subject effects is better, but can be … In our analysis, the frailty correlation
parameter is estimated to … REML, indicating that there is possibly a serial correlation effect …

… Normally, in most clinical applications, survival analysis … frailty model is a random effect
model for time-to-event data, where the random effect (the frailty) has a multiplicative effect …

… In this note we propose a frailty model called piecewise gamma frailty for correlated survival
data with random effects having a nested structure. In frailty models, a dependence function …

… effects and the variance of frailty (cluster/probability sampling unit (PSU)). As can be seen
from the table, the frailty … Therefore, this result shows that there are factors that have an effect …

… Previously, random effects models for survival data have … we develop a method of random
effect analysis of survival data, the … In the model with only a single frailty random effect term, we …