Accurate estimation for extra-Poisson variability assuming random effect models

Abstract

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.

Keywords:

• Extra-Poisson variability components
• random effect models
• negative binomial distribution
• count data
• Bayesian methods

Acknowledgments

The authors are grateful for the comments of the editor and a referee who led to great improvement of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.