Hypothesis Testing in Superiority, Noninferiority, and Equivalence Clinical Trials

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. 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.