Augmented Beta rectangular regression models: A Bayesian perspective.

ABSTRACT: Mixed effects Beta regression models based on Beta distributions have been widely used to analyze longitudinal percentage or proportional data ranging between zero and one. However, Beta distributions are not flexible to extreme outliers or excessive events around tail areas, and they do not account for the presence of the boundary values zeros and ones because these values are not in the support of the Beta distributions. To address these issues, we propose a mixed effects model using Beta rectangular distribution and augment it with the probabilities of zero and one. We conduct extensive simulation studies to assess the performance of mixed effects models based on both the Beta and Beta rectangular distributions under various scenarios. The simulation studies suggest that the regression

SUBMITTER: Wang J 

PROVIDER: S-EPMC5064841 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature