If missing data is not analyzed appropriately, it can lead to major deficiency letters from the FDA (some examples to be provided), which increases the costs and time to approval (or disapproval). So with so many methods available for the analysis of missing data, what is the right way (or FDA approvable way) of analyzing missing data? How can you make the process as painless as possible for both the sponsor and the FDA? In this talk, I will present the top 3 mistakes in the analysis of missing data, and easy ways to avoid them. I will emphasize practical solutions and simple, but often overlooked, ideas for helping your submission pass FDA inspection. Examples and suggestions will be given for a variety of endpoints, focusing on problems commonly seen in medical devices.