The Effective Statistician - in association with PSI

Listen to this episode and learn about the 5 steps to present successfully to your upper management: Determine your goalThink about your audienceStart with the conclusionBe simple but accurateHave the stats as backup and explain them in easy terms, focusing on the most important parts. Train yourself to become a great communicator. Listen to this episode now and share this with your friends and colleagues!

Interview with Swarna Thus, I'm thrilled to talk with Swarna Khare about this topic. Swarna is a long-term listener of the effective statistician and today, it is a great opportunity for her to share with us the ways to think and act more strategic. We answer the following important points: The role of the branding of statistics and how it led Swarna to change from statistics into RWE?What does “working strategically” means for her?What did she do to prepare for this change?What she learned after the switch to RWE?What she recommends to statisticians to become more involved in strategic discussions? Listen to this interesting episode and share this with your friends!

Interview with Paolo Eusebi 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: Find the slides from Paolo here: https://www.psiweb.org/docs/default-source/default-document-library/uncertainty_psi_200827_pe.pptx?sfvrsn=1838dadb_0 View also the webinar about visualization here (only for PSI members): https://www.psiweb.org/vod/item/psi-webinar-using-visualisation-to-help-make-decisions Resources: Cairo, Alberto. The truthful art: Data, charts, and maps for communication. New Riders, 2016.The MU Collective directed by Jessica Hullman and Matt KayWilke, Claus O. Fundamentals of data visualization. O'Reilly Media, 2019.  PSI Visualisation Special Interest Group (VIS SIG)                           Van der Bles et al. "Communicating uncertainty about facts, numbers and science" Royal Society open science 6.5 (2019): 181870.Bonneau et al. "Overview and state-of-the-art of uncertainty visualization." Scientific Visualization. Springer, London, 2014. 3-27.Spaghetti Plots and Hurricanes' Paths                

Interview with Beth Manning 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: Key steps one should consider when driving changeCommon problems people step intoSkills to learn to become a change agent

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/

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!

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

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.

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/ 

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!