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    Rights statement: This is the author’s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 67, 2018 DOI: 10.1016/j.tourman.2017.11.011

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Bayes factors vs. P-values

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Bayes factors vs. P-values. / George Assaf, A.; Tsionas, Mike.
In: Tourism Management, Vol. 67, 08.2018, p. 17-31.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

George Assaf, A & Tsionas, M 2018, 'Bayes factors vs. P-values', Tourism Management, vol. 67, pp. 17-31. https://doi.org/10.1016/j.tourman.2017.11.011

APA

George Assaf, A., & Tsionas, M. (2018). Bayes factors vs. P-values. Tourism Management, 67, 17-31. https://doi.org/10.1016/j.tourman.2017.11.011

Vancouver

George Assaf A, Tsionas M. Bayes factors vs. P-values. Tourism Management. 2018 Aug;67:17-31. Epub 2018 Jan 8. doi: 10.1016/j.tourman.2017.11.011

Author

George Assaf, A. ; Tsionas, Mike. / Bayes factors vs. P-values. In: Tourism Management. 2018 ; Vol. 67. pp. 17-31.

Bibtex

@article{8ea36335f3204db69c15ae5024fc98dc,
title = "Bayes factors vs. P-values",
abstract = "The use of p-values for hypothesis testing has always been the norm in the tourism literature. This paper proposes the use of Bayes factors as an attractive alternative for hypothesis testing. As the Bayes factor is based on the Bayesian approach, which relies solely on the observed sample to provide direct probability statements about the parameters of interest, it is more suited for the purpose of hypothesis testing. Importantly, in this paper we show that the Bayes factor has nicer properties than the p-value, a fact that should be of interest irrespective of whether the user is Bayesian or not. We discuss in more details the advantages of Bayes factors, and provide several interesting recommendations throughout the paper.",
author = "{George Assaf}, A. and Mike Tsionas",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 67, 2018 DOI: 10.1016/j.tourman.2017.11.011",
year = "2018",
month = aug,
doi = "10.1016/j.tourman.2017.11.011",
language = "English",
volume = "67",
pages = "17--31",
journal = "Tourism Management",
issn = "0261-5177",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Bayes factors vs. P-values

AU - George Assaf, A.

AU - Tsionas, Mike

N1 - This is the author’s version of a work that was accepted for publication in Tourism Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Tourism Management, 67, 2018 DOI: 10.1016/j.tourman.2017.11.011

PY - 2018/8

Y1 - 2018/8

N2 - The use of p-values for hypothesis testing has always been the norm in the tourism literature. This paper proposes the use of Bayes factors as an attractive alternative for hypothesis testing. As the Bayes factor is based on the Bayesian approach, which relies solely on the observed sample to provide direct probability statements about the parameters of interest, it is more suited for the purpose of hypothesis testing. Importantly, in this paper we show that the Bayes factor has nicer properties than the p-value, a fact that should be of interest irrespective of whether the user is Bayesian or not. We discuss in more details the advantages of Bayes factors, and provide several interesting recommendations throughout the paper.

AB - The use of p-values for hypothesis testing has always been the norm in the tourism literature. This paper proposes the use of Bayes factors as an attractive alternative for hypothesis testing. As the Bayes factor is based on the Bayesian approach, which relies solely on the observed sample to provide direct probability statements about the parameters of interest, it is more suited for the purpose of hypothesis testing. Importantly, in this paper we show that the Bayes factor has nicer properties than the p-value, a fact that should be of interest irrespective of whether the user is Bayesian or not. We discuss in more details the advantages of Bayes factors, and provide several interesting recommendations throughout the paper.

U2 - 10.1016/j.tourman.2017.11.011

DO - 10.1016/j.tourman.2017.11.011

M3 - Journal article

VL - 67

SP - 17

EP - 31

JO - Tourism Management

JF - Tourism Management

SN - 0261-5177

ER -