Inference in Mixed Proportional Hazard Models with K Random Effects
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.
|Date of creation:||2009|
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- Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008.
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- Bernhard Boockmann. & Dragana Djurdjevic. & Guillaume Horny. & François Laisney., 2009. "Bayesian estimation of Cox models with non-nested random effects: an application to the ratification of ILO conventions by developing countries," Working papers 249, Banque de France.
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