Innovation

Interview with Paolo Eusebi

Our job as statisticians focuses primarily on the analysis and communication of uncertainty in its many aspects. For this episode, I think of uncertainty as the variability in the population we are studying, the uncertainty around estimates, or the model uncertainty, which we might capture via looking into various models.

Interestingly, the visualization of uncertainty – one of the primary forms we use to communicate it – is a rather unknown field. In this episode, I’m very excited to speak with Paolo Eusebi, who has done research in this field to answer the following questions:

• What can we learn from examples outside of medical research? How is it explained to the general public?
• What’s the current status in medical research?
• How can we become better in communication of uncertainty?
• What are further excellent resources regarding the display uncertainty?

Listen to this episode and learn more:

Interview with Beth Manning

What is change management? Is it only something for big corporate initiatives or does it also apply to smaller changes?
Why does it require so much consideration?
What’s hard about change?

Change management is something I never thought about being interesting for statisticians, but recently, I needed to dive in to this frequently. I learned that this helps me when creating new designs or processes as it answers lots of questions about getting from an idea to an implementation.

So today, I’m glad I have a great colleague with me who is an expert on change management and has helped me a lot to drive changes within a big organization.

Listen to this episode and learn the following points:

I still can’t believe how fast things happened, and I am truly grateful for all of this. I interviewed a lot of people who have the same goal as mine – that is to build our expertise. I learned a lot and how important it is to know where the people I interview are coming from and how important it is to adapt my language to theirs.

In this episode, let’s dive in the 2 learnings I had:

Part 2

• Do you want to review a data visualization effectively?
• Do you want to provide your organization with a simple tool to improve your data visualizations?
• Do you need a checklist for yourself to make sure you covered everything for your data visualization?

This episode is for you!

Part 1

• Do you want to review a data visualization effectively?
• Do you want to provide your organization with a simple tool to improve your data visualizations?
• Do you need a checklist for yourself to make sure you covered everything for your data visualization?

This episode is for you!

Interview with Björn Bornkamp and Kaspar Rufibach

Principal stratification used to play a role only in observational research but at least since the addendum of the ICH E9 guideline, this approach to causal inference became a hot topic.

In this episode, I talk with 2 experts from Novartis and Roche. We cover the following questions:

• What is Principal Stratification?
• How would you describe principal stratification to a non-statistician?
• Where do you see the benefits of this estimand compared to the other typical strategies?
• Which critique points do are usually raised against this approach?
• How do you implement/calculate corresponding estimates for this estimand?
• What references would you recommend for further reading?

Björn and Kaspar recommend the following very useful references: