Statistical methodology for the analysis of incomplete data in non-inferiority clinical trials.

Statistical methodology for the analysis of incomplete data in non-inferiority clinical trials.

The aim of this research is to develop new statistical methods for the analysis of incomplete data in non-inferiority clinical trials with binary outcomes. While incomplete data analysis of superiority clinical trials has been excessively discussed in literature, and a number of methods have been proposed to overcome missing data problems, little was done for non-inferiority framework. We propose the development of novel statistical methods that will be applied specifically to non-inferiority clinical trials. At the first step, we will use the requested studies information to set up simulations, which would help us to understand the missing data structure in these studies. Based on the simulations results, we will then develop statistical methods for the analysis of incomplete data. It should be noted, that the goal of our research is purely statistical, with no intention to address any unmet medical needs. Our research will provide new statistical tools, which would be applicable to future non-inferiority clinical trials with binary outcomes. Due to the lack of regulatory guidelines regarding analysis of incomplete data in non-inferiority setting, our research will make a significant contribution to the clinical studies researchers. Once the new statistical methodology is available it will be freely accessible to public, including an open source statistical package which could be used when performing the actual analysis.