Sample Size Calculation: A Step-by-Step Guide
2026-05-01 • 8 min
Quick Answer
Sample size calculation combines expected effect size, outcome variability, significance level, and statistical power. Correct inputs prevent underpowered studies that miss true effects and oversized studies that waste resources. Protocol-ready planning also includes dropout allowance and sensitivity checks.
Core Inputs You Must Specify
Power analysis requires alpha, desired power, anticipated effect, and dispersion estimate. Each assumption must be justified using pilot data, literature, or clinically meaningful thresholds.
Adjusting for Real-World Attrition
Most studies lose participants over time. Add a realistic inflation factor for dropouts, protocol deviations, and subgroup plans. Failure to adjust creates hidden underpower.
Documenting Assumptions
Include all power assumptions in your protocol and report. Reproducible sample-size reasoning improves ethics review quality and publication acceptance.
Frequently Asked Questions
Can I use published effect sizes directly?
Use them as a starting point, but evaluate population and outcome differences before adopting them in your own calculation.
Should I add margin for missing data?
Yes. Always adjust calculated sample size for expected attrition or incomplete records.