Variance component models for survival data

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 frailtymodels inspired by Yashin et al 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 eects of genetic and environmental factors on mortality