Statistical graph for the evaluation of the primary endpoint in a clinical trial

Music City Center 

An assumed treatment effect for a primary endpoint in a randomized clinical trial is determined during the sample size determination process in the planning stage. This effect is an interpretable alternative to the null hypothesis, which posits no effect. To interpret trial results, it is important to evaluate the primary endpoint based on the alternative hypothesis and estimated value of the treatment effect. Nevertheless, most researchers conducting randomized clinical trials on superiority have focused on statistical significance. We propose a quantitative statistical graph, referred to as the "ABC plot," which represents the alternative hypothesis, Bayes factor comparing the null hypothesis with the alternative hypothesis, and confidence interval function for the treatment effect, enhancing the visual evaluation of the treatment effect based on the results of the primary endpoint. We extend it to incorporate the minimum treatment effect used in clinical practice. We apply the proposed graph to a clinical study and demonstrate its usefulness as a statistical tool.

alternative hypothesis

Bayes factor

confidence interval function

clinical trial

primary endpoint

statistical graph 

Biometrics Section