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Biostatistics Advance Access originally published online on September 15, 2008
Biostatistics 2009 10(2):245-257; doi:10.1093/biostatistics/kxn031
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

A new serially correlated gamma-frailty process for longitudinal count data

M. Fiocco*, H. Putter and J.C. Van Houwelingen

Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Postzone S-05-P, PO Box 9600, 2300 RC Leiden, The Netherlands m.fiocco{at}lumc.nl

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.

Keywords: Composite likelihood; Correlated frailty; Counting processes; Multivariate gamma distribution; Repeated events; Sandwich estimator; 2-Stage estimation

* To whom correspondence should be addressed.

Received February 25, 2008; revised June 12, 2008; revised July 10, 2008; accepted for publication August 7, 2008.


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