✔ 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

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.

🔗 Bayesmeta R package

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🔗 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.

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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.

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