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dc.contributor.author | Van Niekerk, Janet![]() |
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dc.contributor.author | Bekker, Andriette, 1958-![]() |
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dc.contributor.author | Arashi, Mohammad![]() |
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dc.date.accessioned | 2019-02-05T12:41:24Z | |
dc.date.available | 2019-02-05T12:41:24Z | |
dc.date.issued | 2019-12 | |
dc.description.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. | en_ZA |
dc.description.department | Statistics | en_ZA |
dc.description.librarian | hj2019 | en_ZA |
dc.description.sponsorship | The National Research Foundation (Re:CPRR3090132066 No 91497 & Re:IFR170227223754 No 109214) and the National Teaching Development (grant no. 11017). | en_ZA |
dc.description.uri | http://journals.sagepub.com/home/smm | en_ZA |
dc.identifier.citation | Van Niekerk, J., Bekker, A. & Arashi, M. 2019, 'Beta regression in the presence of outliers – a wieldy Bayesian solution', Statistical Methods in Medical Research, vol. 28, no. 12, pp. 3729-3740. | en_ZA |
dc.identifier.issn | 0962-2802 (print) | |
dc.identifier.issn | 1477-0334 (online) | |
dc.identifier.other | 10.1177/0962280218814574 | |
dc.identifier.uri | http://hdl.handle.net/2263/68411 | |
dc.language.iso | en | en_ZA |
dc.publisher | Sage | en_ZA |
dc.rights | © The Author(s) 2018 | en_ZA |
dc.subject | Beta regression | en_ZA |
dc.subject | Heterogeneity | en_ZA |
dc.subject | Outlier | en_ZA |
dc.subject | Robust Bayes | en_ZA |
dc.subject | Student's t | en_ZA |
dc.title | Beta regression in the presence of outliers – a wieldy Bayesian solution | en_ZA |
dc.type | Postprint Article | en_ZA |