SURVIVAL ANALYSIS USING A SCALE CHANGE RANDOM EFFECTS MODEL

Frailty models are effective in broadening the class of survival model s and inducing dependence in multivariate survival distributions. In p roportional hazards, the random effect multiplies the hazard function. The scale-change model incorporates unobserved heterogeneity through a random effect that enters the baseline hazard function to change the time scale. We interpret this random effect as frailty, or other unob served risks that create heterogeneity in the population. This model p roduces a wide range of shapes for univariate survival and hazard func tions. We extend this model to multivariate survival data by assuming that members of a group share a common random effect. This structure i nduces association among the survival times in a group and provides al ternative association structures to the proportional hazards frailty m odel. We present parametric and semiparametric estimation techniques a nd illustrate these methods with an example.