Augmented mixed beta regression models with skew-normal independent distributions: Bayesian analysis of labor force data

Abstract

Augmented mixed beta regression models are suitable choices for modeling continuous response variables on the closed interval [0, 1]. The random eeceeects in these models are typically assumed to be normally distributed, but this assumption is frequently violated in some applied studies. In this paper, an augmented mixed beta regression model with skew-normal independent distribution for random effects are used. Next, we adopt a Bayesian approach for parameter estimation using the MCMC algorithm. The methods are then evaluated using some intensive simulation studies. Finally, the proposed models have applied to analyze a dataset from an Iranian Labor Force Survey.

Keywords:

• Augmented Beta distribution
• Beta regression model
• Mixed models
• Skew-normal Independent distribution
• MCMC algorithm

MATHEMATICS SUBJECT CLASSIFICATION:

• 62F15
• 62J05
• 62M10

Acknowledgement

The authors are thankful to the referees for their many helpful comments that greatly improved this paper. We also wish to acknowledge for the support from the Center of Excellence of Spatial Data Analysis of Tarbiat Modares University, Tehran, Iran.