EM Algorithm for Estimating the Parameters of Weibull Competing Risk Model

Abstract

One of the most commonly used models in survival analysis is the additive Weibull model and its generalizations. They are well suited for modeling bathtub-shaped hazard rates that are a natural form of the hazard rate. Although they have some advantages, the maximum likelihood and the least square estimators are biased and have poor performance when the data set contains a large number of parameters. As an alternative, the expectation-maximization (EM) algorithm was applied to estimate the parameters of the additive Weibull model. The accuracy of the parameter estimates and the simulation study confirmed the advantages of the EM algorithm.