Title: Estimating Frailty Models via Poisson Hierarchical Generalized Linear Models
Abstract: AbstractFrailty models extend proportional hazards models to multivariate survival data. Hierarchical-likelihood provides a simple unified framework for various random effect models such as hierarchical generalized linear models, frailty models, and mixed linear models with censoring. Wereview the hierarchical-likelihood estimation methods for frailty models. Hierarchical-likelihood for frailty models can be expressed as that for Poisson hierarchical generalized linear models. Frailty models can thus be fitted using Poisson hierarchical generalized linear models. Properties of the new methodology are demonstrated by simulation. The new method reduces the bias of maximum likelihood and penalized likelihood estimates.Key Words: Hierarchical-likelihoodMarginal likelihoodMultivariate survival dataPenalized likelihood
Publication Year: 2003
Publication Date: 2003-09-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 68
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