Testing for Collinearity using Bayesian Analysis

Assaf, A.G. and Tsionas, M. (2021) Testing for Collinearity using Bayesian Analysis. Journal of Hospitality and Tourism Research, 45 (6). pp. 1131-1141. ISSN 1096-3480

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Abstract

Testing for collinearity continues to be a controversial issue in the literature. Multicollinearity detection criteria, such as the variance inflation factor, often fail to detect the true extent of multicollinearity. In this article, we propose utilizing the Bayesian approach as an attractive alternative. Under the Bayesian approach, we recommend comparing the marginal posterior of regression parameters under two different priors. If the difference in the posterior under these two priors is pronounced, one can surmise that collinearity is harmful. The Kolmogorov–Smirnov test can also be used as further evidence to confirm whether the posterior difference is significant.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Hospitality and Tourism Research
Additional Information:
The final, definitive version of this article has been published in the Journal, Journal of Hospitality & Tourism Research, 45 (6), 2021, © SAGE Publications Ltd, 2021 by SAGE Publications Ltd at the Journal of Hospitality & Tourism Research page: https://journals.sagepub.com/home/jht on SAGE Journals Online: http://journals.sagepub.com/
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1400/1409
Subjects:
ID Code:
163305
Deposited By:
Deposited On:
10 Dec 2021 17:46
Refereed?:
Yes
Published?:
Published
Last Modified:
11 May 2022 07:27