A general formulation of Mixed Proportional Hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. We then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the behavior of the estimator is assessed and I provide an application to the ratification of ILO conventions. Compared to other procedures, the results indicate an important decrease in computing time, as well as improved convergence and stability.
Inference in Mixed Proportional Hazard Models with K Random Effects
Classification JEL : C13, C14, C41.
Keywords : EM algorithm, penalized likelihood, partial likelihood, frailties.
Updated on: 06/12/2018 11:00