The Effective Statistician - in association with PSI

Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry
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Dec 15, 2020 • 44min

Knowledge sharing and what it means for you

Interview with Nelson We also discuss about the following points: What is the role of industry organisations in sharing knowledge?What tools, platforms &/or other approaches can enhance knowledge sharing?Has anything surprised you about setting up your own consultancy?What is the future role of subscription-based publishing in journals? References: Latest article: Getting Started with CDPsWebsite: https://octaconsulting.comLinkedIn: https://www.linkedin.com/in/nelson-kinnersley-3b31435/
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Dec 8, 2020 • 35min

2 learnings from 150 episodes and an Important announcement

In this episode, let's dive in the 2 learnings I had: How marketing helps me in my jobCommunication skillsTelling storiesListening to the needsSelling and influencingChange managementHow having personal and team vision helps meHow to stay on trackGoals and achievement through persistenceTake others with youHow expanding my team helped me a lot Listen to this amazing episode and share this with your friends who can learn and get inspired from this!
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Nov 30, 2020 • 18min

Good data visualization checklist

Part 2 I'm reviewing the first page of the awesome Novartis cheat sheet on data visualization. Click here to get your download of the sheet! Given that this is especially helpful in a visual way, I have recorded this as a video. Have fun watching and please forward it to your colleagues. https://www.youtube.com/watch?v=bQMCMAfBva8
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Nov 23, 2020 • 36min

Good data visualization checklist

Part 1 I'm reviewing the first page of the awesome Novartis cheat sheet on data visualization. Click here to get your download of the sheet! Given that this is especially helpful in a visual way, I have recorded this as a video. Have fun watching and please forward it to your colleagues.
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Nov 16, 2020 • 37min

A deep dive into principal stratification and causal inference

Interview with Björn Bornkamp and Kaspar Rufibach 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: References: Books:Introduction into potential outcomes and causal inference: https://www.cambridge.org/core/books/causal-inference-for-statistics-social-and-biomedical-sciences/71126BE90C58F1A431FE9B2DD07938ABHernan and Robins: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ Pearl, the book of why: https://www.amazon.de/Book-Why-Science-Cause-Effect/dp/046509760XPapers:Paper draft: https://arxiv.org/abs/2008.05406 with markdown: https://oncoestimand.github.io/princ_strat_drug_dev/princ_strat_example.html and github: https://github.com/oncoestimand/princ_strat_drug_devMagnusson et al (Siponimod Beispiel): https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8333 and the corresponding EPAR: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-evaluation-anticancer-medicinal-products-man-revision-5_en.pdfOncology estimand working group: http://www.oncoestimand.org/ 
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Nov 11, 2020 • 40min

The benefit-risk tolerability measure - a new way to reach insights into benefit-risk and more

Interview with Yves Schymura 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: What is the benefit-risk tolerability measure?How can we use the information on which patient discontinue to inform the benefit-risk assessment?How does the model help us rank adverse events in order of their importance?Which adverse events cannot be classified with the model?How to use the model to inform relevant difference for efficacy endpoints? Listen to this episode and share it with your friends and colleagues!
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Nov 2, 2020 • 45min

What we can learn from Taylor Swift about creating data visualizations

Interview with Nicholas Lowthorpe Join us in today's episode as we are talking about the following points: LyricAnswerQuestion"Cherry lips, crystal skiesI could show you incredible things."Taylor talks of her mastery of colour, as she alludes to the incredible insights she can display through just a splash of red against a crystal-clear background.What are your key learnings regarding colour?"Find out what you wantBe that girl for a month."Unlike many data projects, Taylor's will succeed - because she takes the time to find out what her stakeholders want, and agrees clear deadlines.How does your practice look like to learn about the needs of the stakeholders?"So it's gonna be forever or it's gonna go down in flames."Unlike many data projects, Taylor's will succeed - because she takes the time to find out what her stakeholders want, and agrees clear deadlines.How does your practice look like to learn about the needs of the stakeholders?"But I've got a blank space, babyAnd I'll write your name."Taylor's only mistake. My advice would be to leave that space blank and clutter free.How do you measure the success of your visualization? Reference blog: https://www.linkedin.com/feed/update/urn:li:activity:6709808936557580289/ Listen to this episode now and share this with your friends and colleagues!
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Oct 26, 2020 • 44min

How to improve your work by applying the principles of design thinking

Interview with Victoria Gamerman In this episode, Victoria and I talk about the following points: What is design thinking?Why is it important?What are the different aspects of design thinking?What are the examples for application of design thinking within data science and statistics? Reference: Design Thinking Comes of Age
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Oct 20, 2020 • 15min

How to convince someone you have never met before

Very tricky situation! In this episode, I will show you through this example how you can get what you need and have the other person feel good about it. Does this sound like manipulation? No, this is finding a common way that helps everybody.  Listen to this episode now and share this with your friends and colleagues!
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Oct 12, 2020 • 51min

What statisticians can learn from “The Art of Action”

Interview with Stephen Bungay In this episode, you will take a lot of learnings for your everyday life. Specifically, we also discuss the following: How did the Romans and French organize their military?What can we learn from the military's way?How to give support and boundaries the right way?How to take action?How to achieve good results? Listen to this episode to learn more and share this with your friends and colleagues.

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