Sample size estimation and power analysis for clinical research studies

TLDR

Sample size determination is essential for ensuring adequate power while avoiding unnecessary expense and participant exposure. This paper outlines key principles for calculating power and sample size across various applied study designs. The authors detail sample size formulas for single‑group means, surveys, two‑group comparisons of means or proportions, correlation studies, and case‑control categorical outcomes.

Abstract

Determining the optimal sample size for a study assures an adequate power to detect statistical significance. Hence, it is a critical step in the design of a planned research protocol. Using too many participants in a study is expensive and exposes more number of subjects to procedure. Similarly, if study is underpowered, it will be statistically inconclusive and may make the whole protocol a failure. This paper covers the essentials in calculating power and sample size for a variety of applied study designs. Sample size computation for single group mean, survey type of studies, 2 group studies based on means and proportions or rates, correlation studies and for case-control for assessing the categorical outcome are presented in detail.