Variance components models for survival data

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Abstract
Extensions of the Cox proportional hazards model for survival data are studied where allowance is made for unobserved heterogeneity and for correlation between the life times of several individuals. The extended models are frailty models inspired by Yashinet al. (1995). Estimation is carried out using the EM algorithm. Inference is discussed and potential applications are outlined, in particular to statistical research in human genetics using twin data or adoption data, aimed at separating the effects of genetic and environmental factors on mortality.