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.