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Beta regression in the presence of outliers - A wieldy Bayesian solution.
- Source :
-
Statistical Methods in Medical Research . Dec2019, Vol. 28 Issue 12, p3729-3740. 12p. - Publication Year :
- 2019
-
Abstract
- Real phenomena often leads to challenges in data. One of these is outliers or influential values. Especially in a small sample, these values can have a major influence on the modeling process. In the beta regression framework, this issue has been addressed mainly in two ways: the assumption of a different response model and the application of a minimum density power divergence estimation (MDPDE) procedure. In this paper, however, we propose a simple hierarchical Bayesian methodology in the context of a varying dispersion beta response model that is robust to outliers, as shown through an extensive simulation study and analysis of two real data sets. To robustify Bayesian modeling, a heavy-tailed Student's t prior with uniform degrees of freedom is adopted for the regression coefficients. This proposal results in a wieldy implementation procedure which avails practical use of the approach. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09622802
- Volume :
- 28
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Statistical Methods in Medical Research
- Publication Type :
- Academic Journal
- Accession number :
- 138612389
- Full Text :
- https://doi.org/10.1177/0962280218814574