What separates strong clinical research from misleading conclusions? Often, it comes down to study design. In this episode of the Clinical Trial Podcast, Kunal Sampat sits down with Dr. Thomas Newman, Professor of Epidemiology and Biostatistics at UCSF and co-author of Designing Clinical Research, to break down how observational studies actually work. While randomized controlled trials are often considered the gold standard, observational studies are essential in many real-world settings. But they come with challenges including bias, confounding, and misinterpretation that can lead to flawed conclusions if not handled correctly. Dr. Newman shares a practical framework to help you design better studies, interpret results more critically, and build a stronger foundation in clinical research. In this episode, you'll learn: When observational studies are more appropriate than randomized trials A practical framework for designing observational research Key threats to validity: bias, confounding, and chance How to interpret associations vs. causal effects Strategies for dealing with confounders in analysis How to approach statistics with more clarity and confidence About the guest: Dr. Thomas Newman, MD, MPH, is a Professor of Epidemiology and Biostatistics at the University of California, San Francisco. His work focuses on applying epidemiologic methods to important clinical problems in child health, including neonatal jaundice, infections in newborns, and cholesterol screening. He is widely recognized for his contributions to clinical research education and is co-author of Designing Clinical Research and Evidence-Based Diagnosis. Why this episode matters: If you want to grow in clinical research, you need more than surface-level knowledge - you need to understand how studies are designed and where they can go wrong. This episode helps you think like a clinical researcher.

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