Beta-binomial/Poisson models have been used by many authors to model multivariate count data. Lora and Singer [Stat. Med. 27 (2008) 3366–3381] extended such models to accommodate repeated multivariate count data with overdipersion in the binomial component. To overcome some of the limitations of that model, we consider a beta-binomial/gamma-Poisson alternative that also allows for both overdispersion and different covariances between the Poisson counts. We obtain maximum likelihood estimates for the parameters using a Newton–Raphson algorithm and compare both models in a practical example.
Publié le : 2011-07-15
Classification:
Bivariate counts,
longitudinal data,
overdispersion,
random effects,
regression models
@article{1301577155,
author = {Lora, Mayra Ivanoff and Singer, Julio M.},
title = {Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters},
journal = {Braz. J. Probab. Stat.},
volume = {25},
number = {1},
year = {2011},
pages = { 218-235},
language = {en},
url = {http://dml.mathdoc.fr/item/1301577155}
}
Lora, Mayra Ivanoff; Singer, Julio M. Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters. Braz. J. Probab. Stat., Tome 25 (2011) no. 1, pp. 218-235. http://gdmltest.u-ga.fr/item/1301577155/