A tool used in statistical analysis determines the minimum number of participants required to confidently demonstrate that a new treatment or intervention is not substantially worse than an existing standard treatment by a pre-specified margin. For example, a researcher might use this tool to determine how many patients are needed to show that a new drug for hypertension is not significantly less effective than a current market leader.
Determining the appropriate number of participants is critical for the validity and reliability of research findings. An insufficient sample size can lead to inaccurate conclusions, while an excessively large sample size can be wasteful of resources. This methodology helps researchers strike a balance between statistical power and practical feasibility. Historically, ensuring adequate sample size has been a cornerstone of robust clinical trials and research studies across various fields, supporting evidence-based decision-making in healthcare, engineering, and other disciplines.
