In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.

中文翻译：

---

假设随机效应模型的额外泊松变异性的准确估计

在本研究中，假设贝叶斯方法下的随机效应模型估计了额外泊松变异性的分量。估计额外泊松变异性的标准现有方法假设负二项式分布。获得的结果表明，与使用负二项分布相比，使用所提出的随机效应模型可以获得更准确的泊松外变异性分量估计，因为负二项分布只能估计泊松外变异性的一个分量. 考虑到真实数据集，介绍了一些说明性示例。