Browser tool · Statistics
Power & sample size
Explore the relationship between effect size, sample size, and statistical power.
Open app ↗A regression power calculator for continuous linear and binary logistic outcomes, with either a continuous or categorical predictor.
What you can explore
Set the effect size, significance level, target power, and planned sample size. Adjust the design effect, analysis share, and correlation with covariates to reflect your assumptions.
For categorical predictors in logistic models, switch between odds ratios and log-odds coefficients without changing the underlying effect.
How it works
The calculator uses Fisher information and large-sample Wald approximations. With several categories, results are separate category-versus-base contrasts, not an omnibus test. Consequential study designs should be confirmed by simulation.
Calculations run in your browser. No account or upload is required.