Scaled Consistent Estimation of Regression Parameters in Frailty Models

Abstract

A computationally attractive method of estimation of parameters for a class of frailty regression models is discussed. The method uses maximum likelihood estimation for the classical exponential regression model. Scaled Fisher consistency is shown to hold and a simulation study indicating good asymptotic properties of the method, as well as real data case analysis, are presented.