Correlated versus uncorrelated frailty Cox models: A comparison of different estimation procedures.
In many studies in medicine, including clinical trials and epidemiological investigations, data are clustered into groups such as health centers or herds in veterinary medicine. Such data are usually analyzed by hierarchical regression models to account for possible variation between groups. When such variation is large, it is of potential interest to explore whether additionally the effect of a within-group predictor varies between groups. In survival analysis, this may be investigated by including two frailty terms at group level in a Cox proportional hazards model. Several estimation methods have been proposed to estimate this type of frailty Cox models. We review four of these methods, apply them to real data from veterinary medicine, and compare them using a simulation study.
Department of Statistics, Faculty of Science, University of Misurata, Misurata, Libya. aelghafghuf@upei.ca.|Centre for Veterinary Epidemiological Research, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada. aelghafghuf@upei.ca.
Adel
A
Elghafghuf
Centre for Veterinary Epidemiological Research, University of Prince Edward Island, Charlottetown, PE, C1A 4P3, Canada.
Henrik
H
Stryhn
D000818:Animals; D003198:Computer Simulation; D006801:Humans; D016016:Proportional Hazards Models; D016019:Survival Analysis; D014730:Veterinary Medicine / Q000379:methods*
Correlated frailty Cox model; Estimation procedures; Frailty models; Multilevel survival analysis; Poisson modeling approach; Simulation study