Michael Harhay, PhD, MPH, Assistant Professor of Epidemiology and Medicine, has co-authored a new review, “Bayesian Statistics for Clinical Research,” published in The Lancet. The article offers a detailed comparison of the philosophical and methodological differences between Bayesian and frequentist approaches to data analysis. While frequentist statistics dominated medical practice in the 20th century, advancements in computing have made Bayesian analysis more accessible and valuable across disciplines, particularly in medical research.
Bayesian methods enhance data interpretation in studies designed with frequentist principles and offer a more informative foundation for clinical trial design. As familiarity with Bayesian inference grows, its intuitive and flexible approach is expected to become even more widely adopted in clinical research.