A new serially correlated gamma-frailty process for longitudinal count data.
We describe a new multivariate gamma distribution and discuss its implication in a Poisson-correlated gamma-frailty model. This model is introduced to account for between-subjects correlation occurring in longitudinal count data. For likelihood-based inference involving distributions in which high-dimensional dependencies are present, it may be useful to approximate likelihoods based on the univariate or bivariate marginal distributions. The merit of composite likelihood is to reduce the computational complexity of the full likelihood. A 2-stage composite-likelihood procedure is developed for estimating the model parameters. The suggested method is applied to a meta-analysis study for survival curves.
Fiocco
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M
Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Postzone S-05-P, PO Box 9600, 2300 RC Leiden, The Netherlands. m.fiocco@lumc.nl
Putter
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Van Houwelingen
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JC
D002277:Carcinoma / Q000401:mortality; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D016013:Likelihood Functions; D008137:Longitudinal Studies; D015201:Meta-Analysis as Topic; D008954:Models, Biological; D015233:Models, Statistical; D015999:Multivariate Analysis; D010051:Ovarian Neoplasms / Q000401:mortality