Course curriculum

First presented at the 2025 PSI Conference in London, this course provides a practical introduction to pooled analyses of clinical trial data, focusing on essential methodologies for clinical trial statisticians. Discover how pooling data enhances the ability to assess efficacy and safety, increases statistical power to detect rare events (e.g., adverse effects), and improves the identification of subgroup effects. Through real-world case studies, you’ll explore strategies for addressing differences between trials and generating more robust clinical insights.

    1. Why Pool Patient-Level Data Across Trials?

    2. Examples of Pooled Patient-Level Analyses

    3. Review: Why Pooling Matters

    1. Review: Simpson's Paradox

    1. Review: Hierarchical Modeling of Trial Data

    2. Exploring Heterogeneity with Trace Plots

    3. Test Your Understanding: Interpreting Trace Plots

    1. Review: Exploring Treatment Effect Heterogeneity

    1. Computer Practical

    2. Solutions

    1. Review: extensions to binary and survival data

About this course

  • €500,00
  • 13 lessons
  • Delivered as a pre-conference course at the 2025 PSI Conference

Instructors

Tim Friede

Professor

Tim Friede is Professor of Biostatistics at the University Medical Center Göttingen, where he leads the Department of Medical Statistics. With experience in academia and industry, he specializes in clinical trial methodology, adaptive designs, and evidence synthesis. Previously, he held roles at Lancaster University, Novartis, and Warwick Medical School. He is an expert in biometry and a member of the Sino-German Institute for Social Computing and the Campus Institute Data Science. Tim is dedicated to advancing statistical methods for clinical research.

Thomas Debray

Founder, Smart Data Analysis and Statistics

Dr. Thomas Debray is a biostatistician specializing in predictive modeling and real-world evidence. With more than a decade of experience across Utrecht University, University College London, and the University of Oxford, he currently serves as a guest scientist at the University Medical Center Göttingen. As the founder of Smart Data Analysis and Statistics, he collaborates with leading pharma and biotech organizations to improve trial design, advance statistical innovation, and translate complex data into evidence that supports regulatory and clinical decision-making. He is the lead editor of the handbook Comparative Effectiveness and Personalized Medicine Research Using Real-World Data, reflecting his focus on bridging modern statistical methodology with practical, real-world applications.

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