Post-hoc Power Calculator
Evaluate statistical power of an existing study
Study Group Design
Two study groups each received different treatments.
The primary endpoint was binomial - only two possible outcomes.
Eg, mortality (dead/not dead), pregnant (pregnant/not)
Dichotomous Endpoint, Two Independent Sample Study
|Incidence, group 1 ||35%|
|Incidence, group 2 ||20%|
|Subjects, group 1 ||150%|
|Subjects, group 2 ||148%|
About This Calculator
This calculator uses a variety of equations to calculate the statistical power of a study after the study has been conducted.1
"Power" is the ability of a trial to detect a difference between two different groups. If a trial has inadequate power, it may not be able to detect a difference even though a difference truly exists. This false conclusion is called a type II error.
Just like sample size calculation, statistical power is based on the baseline incidence of an outcome, the population variance, the treatment effect size, alpha, and the sample size of a study.
The Dangers of Post-Hoc Analysis
Post-hoc power analysis has been criticized as a means of interpreting negative study results.2 Because post-hoc analyses are typically only calculated on negative trials (p ≥ 0.05), such an analysis will produce a low post-hoc power result, which may be misinterpreted as the trial having inadequate power.
As an alternative to post-hoc power, analysis of the width and magnitude of the 95% confidence interval (95% CI) may be a more appropriate method of determining statistical power.
Sample Size Calculation
To calculate an adequate sample size for a future or planned trial, please visit the sample size calculator.
References and Additional Reading
- Rosner B. Fundamentals of Biostatistics. 7th ed. Boston, MA: Brooks/Cole; 2011.
- Levine M, Ensom MH. Post hoc power analysis: an idea whose time has passed? Pharmacotherapy. 2001;21(4):405-9. PMID 11310512