In this episode, I talk with my long-time friend and frequent guest, Kaspar Rufibach, about a skill that quietly determines how much impact we really have: presenting and communicating our work.
We walk through how Kaspar prepares his talks (including why he starts months in advance), how he structures messages so stakeholders actually remember and act on them, and why overcrowded slides are often just a sign that we haven’t done the hard thinking yet.
We also get honest about something many statisticians feel but rarely discuss: the fear of public speaking, the frustration of bad meetings, and the “personal brand” you build every time you present—whether you intend to or not.
If you’ve ever walked out of a meeting thinking “I don’t think they really understood what I meant,” this episode is for you.
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36:23
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36:23
External control arms - how to get to a good one
In this episode, I’m joined by Deepa Jahagirdar, Associate Research Principal at Cytel, to explore what it really takes to build a good external control arm (ECA). Deepa brings a fascinating background from social epidemiology, where causal questions often need to be answered without running randomized trials. That experience translates directly into today’s growing need for ECAs, especially when we rely on real-world data to support single-arm trials, extension phases, or situations where randomization simply isn’t possible.
Together, we discuss how to choose the right data source, how target trial emulation works in practice, what to do about confounding, and how to judge whether an ECA is truly robust. If you’re working with real-world evidence, complex study designs, or causal inference, this episode will give you clarity and confidence in approaching ECAs the right way.
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26:51
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26:51
Top 9: Non-parametric analyses - much more than just the Wilcoxon test!
Why this episode made our all-time Top 9: If you’ve ever thought “non-parametric = Wilcoxon/Mann-Whitney and that’s it,” this conversation will happily destroy that myth. Frank shows how rank-based methods unlock rigorous analyses for skewed data, outliers, ordinal endpoints, small samples, composites/estimands—and how to communicate effects without relying on means.
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40:19
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40:19
How to communicate results from adaptive studies simple, but still correct
Adaptive designs let us learn earlier, stop smarter, and protect patients—but they also make communication tricky. In this episode, Kaspar Rufibach and I dig into what “still correct” looks like when you try to explain results from group-sequential and other adaptive trials to regulators, clinicians, and scientific audiences. We unpack conditional vs. unconditional bias, median-unbiased estimation, stage-wise ordering for p-values, confidence intervals in multi-stage settings, and what to do with secondary endpoints and multiplicity. We also touch on ICHE20 (Adaptive Clinical Trials) and why pre-specification isn’t just a box-tick—it’s what builds trust.
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24:20
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24:20
Introduction to adaptive designs and ICH E20
In this episode, I’m joined once again by my friend and frequent guest, Kaspar Rufibach, to talk about a topic that’s been around for decades but is gaining fresh attention thanks to the new ICH E20 draft guideline—adaptive designs in confirmatory clinical trials.
Kaspar and I discuss why and when we should consider adapting a clinical trial, what kinds of adaptations are statistically valid and meaningful in a regulatory context, and why these designs—despite their efficiency—are still not used as often as they could be.
We also dive into the statistical foundations behind adaptive designs, such as p-value combination methods and meta-analytic thinking, and explore how adaptive approaches can help us make faster and smarter decisions in drug development.
Über The Effective Statistician - in association with PSI
The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.
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