Here you can learn how to add new statistical methods to your toolbox. These may not be neccessarily cutting edge methods, but approaches, that you are not yet aware about.
For years, creating data visualizations has frustrated statisticians, data analysts and data scientists. Software – especially SAS – hasn’t been great and organisation have tried to take the pain out of the process by creating standard figures. But these standard graphics fail to communicate the message to the intended audience in the best way. Great …
Why is it impossible to have a great standard data visualisation? Read More »
Have you been considering a one-armed observational study or asked to work on such a study? As a statistician, it is important to understand the scientific but even more the political background of such studies. In this episode, we will discuss one-armed observational studies and why they are, in most cases, not a good idea. …
The world of healthcare continues to change, and it’s important to keep up with the latest advances in technology and research. That’s why I’m excited to talk with Shirley Wang, one of the leaders of RCT Duplicate, a study focused on duplicating randomized clinical trials through real world data. She is currently leading the RCT Duplicate as the …
Today I’m talking with Rachel Tham, a principal statistician, about a book that has been incredibly impactful in both of our lives—Deep Work. We discuss what deep work is and how it can help statisticians at work. Deep work is a concept developed by Cal Newport which encourages people to focus intensely on one task …
Why are companies often running single arm studies in development? What are the potential drawbacks and why is it not a binary choice between full comparative study and single arm trial? What are solutions in between to find a balance between feasibility and rigour? Single arm studies are a popular method for collecting data despite …
Reproducible research is a key part of research in the pharma industry. It allows for transparency, understanding, and accuracy in the research process. But how can you make your research more reproducible? Today, I talk with Heidi Seibold who has dedicated her career to helping researchers become more reproducible. Let’s take a look at 3 …