TY - JOUR
T1 - Bayesian Analysis of Augmented Mixed Beta Models with Skew-Normal Random Effects
TT - تحلیل بیزی مدلهای رگرسیون بتای آمیختهی افزوده با اثرهای تصادفی چوله-نرمال
JF - srtc-jsri
JO - srtc-jsri
VL - 14
IS - 1
UR - http://jsri.srtc.ac.ir/article-1-256-en.html
Y1 - 2017
SP - 101
EP - 118
KW - Augmented beta regression
KW - beta distribution
KW - mixed models
KW - Bayesian approach
KW - skew-normal distribution.
N2 - Many studies in different areas include data in the form of rates or proportions that should be analyzed. The data may also accept values zero and one. Augmented beta regression models are an appropriate choice for continuous response variables in the closed unit interval [0,1]. The data in this model are based on a combination of three distributions, degenerate distribution at 0 and 1, and a beta density in (0,1). The random effects are usually added to the model for accommodating the data structures as well as correlation impacts. In most of these models, the random effects are generally assumed to be normally distributed, while this assumption is frequently violated in applied studies. In this paper, the augmented mixed beta regression model with skew-normal distributed random effects is presented. A Bayesian approach is adopted for parameter estimation using Markov Chain Monte Carlo method. The proposed model is applied to analyze a real data set from Labor Force Survey.
M3 10.18869/acadpub.jsri.14.1.101
ER -