Identifiability of bivariate frailty models based on additive independent components

Iachine, I. A., Yashin, A. I.
Research Report of the Department of Statistics and Demography 8
12 pages. Odense, Odense University (1998)


Frailty models are used in survival analysis to account for unobserved heterogeneity in individual risks to disease and death. To analyze bivariate data on related survival times (e.g. matched pairs experiments, twin or family data), bivariate correlated frailty models were suggested. In these models related individuals have different but dependent frailties. Such frailties are often constructed using independent additive components with one common component for both frailties. In this paper we show that under weak regularity conditions all bivariate frailty models with frailties constructed from independent additive components are identifiable. (AUTHORS)
The Max Planck Institute for Demographic Research (MPIDR) in Rostock is one of the leading demographic research centers in the world. It's part of the Max Planck Society, the internationally renowned German research society.