Power Calculation (Sample Size)
A statistical calculation performed before a clinical trial begins to determine the minimum number of participants needed to reliably detect a meaningful treatment difference. Adequate statistical power (typically 80-90%) ensures the trial can distinguish a true treatment effect from random variation.
Technical Context
Sample size formula for a superiority trial comparing two means: n per group = 2 × (Zα/2 + Zβ)² × σ² / δ², where Zα/2 = 1.96 for two-sided α = 0.05, Zβ = 0.84 for 80% power (or 1.28 for 90%), σ = standard deviation of the endpoint, and δ = minimum clinically important difference to detect. Example: to detect a 1.5% HbA1c difference (δ) with SD = 1.2% (σ) at 80% power (two-sided α = 0.05): n = 2 × (1.96+0.84)² × 1.44 / 2.25 = 2 × 7.84 × 0.64 = 10 per group. After adjusting for expected dropout (~20%): approximately 13 per group. For cardiovascular outcomes trials with event rates of 3-5%/year, much larger samples are needed (5,000-17,000 patients) because the event rate is the limiting factor. Power calculations must be documented in the protocol and statistical analysis plan.