A new regression model for overdispersed binomial data accounting for outliers and an excess of zeros.

ABSTRACT: Binary outcomes are extremely common in biomedical research. Despite its popularity, binomial regression often fails to model this kind of data accurately due to the overdispersion problem. Many alternatives can be found in the literature, the beta-binomial (BB) regression model being one of the most popular. The additional parameter of this model enables a better fit to overdispersed data. It also exhibits an attractive interpretation in terms of the intraclass correlation coefficient. Nonetheless, in many real data applications, a single additional parameter cannot handle the entire excess of variability. In this study, we propose a new finite mixture distribution with BB components, namely, the flexible beta-binomial (FBB), which is characterized by a richer parameterization. This allow

SUBMITTER: Ascari R 

PROVIDER: S-EPMC8360060 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature