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Statistical methods are a powerful tool used in clinical trials to assess whether the data support evidence of a treatment effect. It is therefore key that the results of any statistical analysis are interpreted correctly. However, understanding and interpreting statistical results can be challenging for non-statisticians.

In this workshop, participants will be introduced to common statistical methods applied to specific outcomes and their results. Some examples of potential statistical concepts to be covered can include commonly seen hypothesis test, survival analyses, regression modelling, MMRM, and adjusting for multiplicity. Important concepts such as p-values will be explained fully. Idealized examples as well as examples from publicly posted FDA reviews and results on clinicaltrials.gov will be used.

Group discussions using example outputs (including examples from FDA reviews) will give participants the opportunity to apply their learning by critically evaluating statistical analysis approaches and interpreting statistical results, thus giving participants the tools necessary to effectively communicate with their colleagues involved in drug development