Essential tips on sample size calculation and biostatistics

Sample size calculation and biostatistical analysis are fundamental to rigorous clinical research, yet many clinician-researchers struggle with appropriate methods. This chapter provides practical, principle-based guidance for non-statisticians on sample size determination and analysis planning. Clearly specified study objectives are the essential foundation. For sample size determination, key considerations include: distinguishing confirmatory from exploratory studies (formal calculation versus sample size rationale); developing a sound analysis plan; selecting appropriate tools; using conservative estimates; defining clinically meaningful effect sizes; accounting for multiplicity; addressing reduced power with co-primary outcomes; and considering approaches for artificial intelligence and machine learning studies. Core principles of biostatistical analysis include: familiarization with statistical software, now facilitated by generative AI; appropriate regression applications; proper handling of missing data; controlling false-positive errors; and distinguishing statistical from clinical significance. These principles apply across common study designs, with clear objectives remaining foundational throughout.