A review of Bayesian hypothesis testing and its practical implementations
Date
2022
Authors
Wei, Zhengxiao
Yang, Aijun
Rocha, Leno
Miranda, Michelle F.
Nathoo, Farouk S.
Journal Title
Journal ISSN
Volume Title
Publisher
Entropy
Abstract
We discuss hypothesis testing and compare different theories in light of observed or
experimental data as fundamental endeavors in the sciences. Issues associated with the p-value
approach and null hypothesis significance testing are reviewed, and the Bayesian alternative based
on the Bayes factor is introduced, along with a review of computational methods and sensitivity
related to prior distributions. We demonstrate how Bayesian testing can be practically implemented
in several examples, such as the t-test, two-sample comparisons, linear mixed models, and Poisson
mixed models by using existing software. Caveats and potential problems associated with Bayesian
testing are also discussed. We aim to inform researchers in the many fields where Bayesian testing
is not in common use of a well-developed alternative to null hypothesis significance testing and to
demonstrate its standard implementation.
Description
Keywords
hypothesis testing, Bayes factor, prior distributions
Citation
Wei, Z., Yang, A., Rocha, L., Miranda, M., & Nathoo, F. (2022). “A review of Bayesian hypothesis testing and its practical implementations.” Entropy, 24(2), 161. https://doi.org/10.3390/e24020161