Correlated time-to-event data are commonly encounted in biomedical research, often as recurrent e v ent data or clustered data. To accommodate the correlation among survival times within the proportional hazards model framework, frailty m o d e l s h a ve beendeveloped. Clustered and recurrent event data may require two frailties, leading to a need for appropriate tests for frailty model select...

background: the study was developed in order to find a subset of potential factors, which affect birth distance pattern, regarding consideration on correlation of events of birth in a family and correlation within clusters/centers which other studies omit these correlations. methods: referring to documents that were registered for family in the health care centers on socio-economical zone, we c...

Biomedical studies often collect multivariate event time data from multiple clusters (either subjects or groups) within each of which event times for individuals are correlated and the correlation may vary in different classes. In such survival analyses, heterogeneity among clusters for shared and specific classes can be accommodated by incorporating parametric frailty terms into the model. In ...

The marginal proportional hazards frailty model for multivariate failure time data characterizes the intracluster dependency with the frailty model while formulating the marginal distributions with the proportional hazards model. The gamma frailty distribution has been widely used to model intracluster dependency because of its simple interpretation and mathematical tractability. Glidden (2000)...

Survival analyses are greatly used in medical research especially frailty models which are mostly used to account for heterogeneity in time-to-event. Over the years treatment of cancer has progressed with some patients being cured from different type of cancer. Survival analysis is more focused on subjects that are less at risk of recurrences, metastasis or death after the first treatment as th...

The dependence between individuals in a group is modeled by the group specific quantity, which can be interpreted as an unobserved covariates or “frailties” common to the individuals in the group and assumed to follow some distribution. We consider the shared frailty model in the frame work of parametric Cox proportional hazard model. The Cox regression model with the shared frailty factor allo...

In this paper, we consider shared frailty model with inverse Gaussian distribution as frailty distribution and log-logistic distribution (LLD) as baseline distribution for bivariate survival times. We fit this model to three real life bivariate survival data sets. The problem of analyzing and estimating parameters of shared inverse Gaussian frailty is the interest of this paper and then compare...

background: cox proportional hazard (cph) model is the most widely used model for survival analysis. when there are unobserved/unmeasured individuals factor, then the results of the cox proportional hazard model may not be reliable. the purpose of this study was to compare the results of cph and frailty models in breast cancer (bc) patients. methods: a historical cohort study was carried out us...