Hypothesis testing in superiority, non-inferiority and equivalence clinical trials: Implications in Physical Medicine and Rehabilitation

Abstract: In medical research, it is important to be able to examine whether there is a significant difference between two samples. With this, establishing an appropriate hypothesis is a critical, basic step for correct interpretation of results in inferential statistical data analysis. It is important to note that the aim of hypothesis testing is not to "accept" or "reject" the null hypothesis but to gauge the likelihood that the observed difference is genuine if the null hypothesis is true. Traditionally, the null hypothesis assumes that there is no statistically significant difference between the two groups. As it has become more difficult to develop new treatments that are better than the standard of care. This review article summarizes and explains the methodology of the different types of clinical trials regarding the relevant basic statistical concepts and hypothesis testing. Corresponding Author: Dinesh Kumbhare, MD, PhD, FRCPC, FAAPMR, Department of Medicine, Division of Physical Medicine and Rehabilitation, University of Toronto, Toronto, Ontario, Canada. Email: dinesh.kumbhare@uhn.ca. Tel: 416-597-3422 x 4612 Funding Source: The authors received no funding for this work. Competing Interests of Authors: None declared Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

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