The Effective Statistician - in association with PSI

Interview with Sam Gardner & Thomas Neitmann What You’ll Learn: ✔ How Thomas and Sam were first introduced to SAS and R — and how their early experiences shaped their preferences. ✔ Key differences in learning curves and the resources available for beginners. ✔ How each tool fares in day-to-day work and long-term maintainability. ✔ Strengths and weaknesses of SAS and R communities — and the events, forums, and support structures that keep them thriving. ✔ The impact of cost, licensing, and open-source vs proprietary models on adoption. ✔ How both tools handle data visualization and producing publication-quality graphics. ✔ Regulatory acceptance: How far R has come in being used for submissions to agencies like the FDA — and what’s still needed for broader acceptance. ✔ Why your choice of tool might also depend on generational trends and the skillsets of new talent entering the field. Why You Should Listen: This isn’t just a technical comparison — it’s a candid, practical discussion based on real-world pharmaceutical research experience. You’ll hear about cultural differences between the SAS and R worlds, the business factors that influence adoption, and the ways companies are moving toward hybrid environments where both can thrive. If you’re making decisions about tools for your team or career, this episode will help you navigate the trade-offs with eyes wide open. Links: 🔗 Thomas' Adventure Blog 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Interview with Stuart McGuire What You’ll Learn: ✔ How to recognize when your “chimp” is in control — and what to do about it ✔ The difference between emotional, rational, and programmed brain responses ✔ How to manage anxiety and fear in high-stakes situations like meetings and presentations ✔ Why we often overwork out of tribal guilt — and how to break that cycle ✔ How false beliefs can be reprogrammed — just like changing default settings in a computer ✔ Why rest, reflection, and celebration are essential for performance Why You Should Listen: Do you ever freeze in meetings, hold back from sharing your opinion, or overwork out of guilt or fear of letting others down? You’re not alone — and there’s a reason why. This episode will help you: Understand your emotional triggers Reframe your reactions in high-pressure situations Build better habits for communication, leadership, and resilience And most importantly, take back control of your mindset Whether you’re presenting to leadership, leading a project, or just navigating stress — The Chimp Paradox can equip you with the tools to respond more intentionally and perform at your best.

Interview with Yannis Jemiai & Rajat Mukherjee What You’ll Learn: ✔ How two leading statisticians transitioned into data science ✔ The key differences (and overlaps) between data science, statistics, big data, and machine learning ✔ Why data science is more than hype—and why statisticians are needed more than ever ✔ The role of visualization and statistical learning in interpreting high-dimensional biomedical data ✔ Real-world applications of data science in biomarker discovery, precision medicine, and pharmacovigilance ✔ What makes data science in pharma different from tech giants like Google or Amazon ✔ Tips for statisticians who want to get started in data science Why You Should Listen: If you're a statistician wondering whether data science is your next career step—or simply curious about how the two fields intersect—this episode offers an honest, expert-led exploration. Yannis and Rajat pull back the curtain on what data science really involves, how it's transforming pharma and healthcare, and what skills and mindset statisticians can bring to this evolving space. Links: 🔗 Explore Cytel’s data science insights and case studies 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Interview with Rachel Tham What You’ll Learn: ✔ Why “index date” is more complicated than it sounds ✔ Common mistakes around exposure definitions ✔ The importance of understanding how RWE data is generated ✔ What programmers should know about timing, variables, and algorithms ✔ Why project management in RWE must be iterative and stakeholder-driven ✔ Key terminology pitfalls that can trip up even experienced professionals ✔ How data issues like duplicates, implausible values, and partial dates impact analyses ✔ Best practices for communication, timelines, and managing expectations in RWE projects Why You Should Listen: If you're working in real-world evidence or thinking of transitioning from clinical trials, this episode is packed with practical advice to help you avoid common mistakes and set your projects up for success. Rachel shares from her own hands-on experience—starting from data management and programming to leading statistical analyses in RWE. Alexander and Rachel also highlight real-world data quirks that no textbook prepares you for, making this episode an essential resource for statisticians, data scientists, and healthcare researchers alike. Links: 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Manjari Narayan, a speaker at the Effective Statistician Conference 2024, dives into the transformative impact of AI on biotechnology and drug development. She discusses the untapped opportunities for statisticians to innovate before clinical trials and the challenges posed by AI-guided experiments. Manjari emphasizes the importance of experimental design, decision-making, and the need to rethink biomarker discovery. She also encourages embracing generalism and risk-taking for career growth, highlighting strategies for expanding professional opportunities.

Keynote by Prof. Tim Friede | The Effective Statistician Conference 2024 What You’ll Learn: ✔ When and how to combine RCTs with real-world data (RWD) ✔ The CJD study: lessons from combining registry and trial data ✔ Hierarchical Bayesian meta-analysis and shrinkage estimators ✔ Robustness of these approaches in the face of heterogeneity ✔ Practical coding tips using the bayesmeta R package ✔ Design strategies for prospective data integration ✔ Regulatory perspectives on RWD-supported evidence Why You Should Listen: If you’re working in rare diseases, pediatrics, or situations where large-scale RCTs are not feasible, this episode offers practical tools and methodological clarity. Tim’s approach helps statisticians create more informative and reliable evidence from limited data—crucial for both research impact and regulatory engagement. Resources & Links: 🔗 Bayesmeta R package 🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician. 🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills. 🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine. 🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities. If you’re working on evidence generation plans or preparing for joint clinical advice, this episode is packed with insights you don’t want to miss. Join the Conversation:Did you find this episode helpful? Share it with your colleagues and let me know your thoughts! Connect with me on LinkedIn and be part of the discussion. Subscribe & Stay Updated:Never miss an episode! Subscribe to The Effective Statistician on your favorite podcast platform and continue growing your influence as a statistician.

Sebastian Schneeweiss, a Harvard Medical School professor specializing in medicine and epidemiology, shares insights on emulating randomized trials with real-world data. He discusses the motivation behind this approach, emphasizing its significance for regulatory-grade evidence. Topics include the challenges of data quality and adherence, use cases for real-world evidence in expanding treatment indications, and the innovative ‘Benchmark-Calibrate-Extrapolate’ strategy. This conversation is a must-listen for those in biostatistics, epidemiology, and healthcare innovation.

Discover the transformative power of genuine networking, driven by curiosity rather than small talk. Learn to set clear intentions for building meaningful connections at events. Uncover myths that may hold you back and develop strategies to overcome them. Get practical advice specifically for conference attendees, ensuring you network with confidence. Embrace the idea that authentic relationships with peers and mentors can unlock unexpected career opportunities and foster personal growth.

Emma Crawford, an autism advocate and leader in workplace inclusion, shares personal insights into navigating autism in professional settings. She emphasizes the critical need for inclusive work cultures and proactive leadership that seeks feedback. Topics include embracing neurodiversity, the role of technology in accessibility, and the importance of kindness in leadership. Emma calls for a shift in attitudes towards disability, encouraging workplaces to become environments where everyone feels empowered to express their needs.

Anna Forsythe, a Pharmacologist and healthcare economist, is the founder of Oncoscope, which automates systematic literature reviews to enhance cancer treatment decisions. In this conversation, she explores how daily updates in literature reviews can revolutionize oncology. Anna discusses the balance between innovation and clinical responsibility, and the introduction of AI in improving SLR accuracy. She shares insights on making cancer data accessible to patients and her commitment to altruistic ventures that prioritize patient care over profit.