Common statistical pitfalls in clinical research: The guide to avoid misinterpreting p values, confidence intervals, odds ratios, and more

ABSTRACT Most clinical research relies on frequentist statistics—a framework that, while widely used, is not intuitive and susceptible to profound misinterpretation. Common misinterpretations arise when frequentist concepts such as confidence intervals are interpreted through the more-intuitive Bayesian lens, leading to false conclusions and misinformation that can spread unchecked. Even among researchers with formal statistics training, frequentist statistics demands deliberate study and review to avoid navigate prevalent analytic pitfalls. This guide aims to offer an approachable, practical, and consummate study of the most common statistical pitfalls encountered in clinical research. From p values, confidence intervals, and odds ratios, to the “Table 2 fallacy,” we hope this article will be a foundational resource for both learners and seasoned researchers seeking to enhance methodologic and analytic rigor of clinical research.