Bayesian techniques, as an alternative method of statistical analysis in rehabilitation studies, have some advantages such as handling small sample sizes, allowing incorporation of previous experience of the researchers or clinicians, being suitable for different kinds of studies, and managing highly complex models. These characteristics are important in rehabilitation research. In the present article, the Bayesian approach is displayed through three examples in previously analyzed data with traditional or frequentist methods. The studies used as examples have small sample sizes and show that the Bayesian procedures enhance the statistical information of the results. The Bayesian credibility interval includes the true value of the corresponding parameter diminishing uncertainty about the treatment effect. In addition, the Bayes factor value quantifies the evidence provided by the data in favor of the alternative hypothesis as opposed to the null hypothesis. Bayesian inference could be an interesting and adaptable alternative statistical method for physical medicine and rehabilitation applications.
From the Department of Mathematics, Universidade da Coruña, A Coruña, Spain (AQ-d-R); Department of Physiotherapy, Medicine and Biomedical Sciences, Universidade da Coruña, A Coruña, Spain (BR-R, VR-G, JC-M, AM-R); and Department of Physical and Sports Education, Universidade da Coruña, A Coruña, Spain (PA-R).
All correspondence should be addressed to: Alejandro Quintela-del-Río, PhD, Faculty of Physiotherapy, University of A Coruña, Campus de Oza, s/n 15071, A Coruña, Spain.
Financial disclosure statements have been obtained, and no conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.