Inference in Mixed Proportional Hazard Models with K Random Effects

Guillaume Horny

Working papers from Banque de France

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. 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.

Keywords: EM algorithm; penalized likelihood; partial likelihood; frailties. (search for similar items in EconPapers)
JEL-codes: C13 C14 C41 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2009
New Economics Papers: this item is included in nep-ecm and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Inference in mixed proportional hazard models with K random effects (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:bfr:banfra:248

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