Inference in mixed proportional hazard models with <Emphasis Type="Italic">K</Emphasis> random effects |
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Authors: | Guillaume Horny |
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Institution: | (1) BETA, University Louis Pasteur (Strasbourg I), 61 avenue de la Forêt Noire, Strasbourg Cedex, 67085, France |
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Abstract: | 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. I 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. |
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Keywords: | EM algorithm Penalized likelihood Partial likelihood Frailties Duration analysis |
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