Archives for November 2020

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:

Interview with Yves Schymura

Yves and I have worked together in various roles. Over time, he became more interested in becoming a statistician and I helped him to change his career path in this direction.

As part of his master thesis, he worked on an idea; I had sketched out a couple of years ago but never had the time to fully think through. I wanted to explore how we could utilize existing study data to inform the benefit-risk assessment of different therapies. In this episode, you will learn a new concept which also is related to minimal clinical meaningful differences and helps to assess the impact of various adverse events on the patient. Specifically, we dive into:

Interview with Nicholas Lowthorpe

Today, we are talking about Taylor Swift and visualizations.
Does it seem like a very unreasonable thing?
I thought so as well but then I read this interesting LinkedIn post where I laughed hard but it really made sense!

Join us in today’s episode as we are talking about the following points: