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Power calculations help assess decision probabilities under assumptions during study planning. After results are known, calculating power using the observed effect does not independently explain an uncertain finding or provide new evidence about whether the treatment truly works.
Define the question and assumptions
Report planned power separately from realised sample size, events and data quality. Interpretation should consider effect magnitude, confidence intervals and design limitations. A low power value calculated from a small observed difference does not independently establish either no effect or definite study inadequacy. Explain the purpose of each quantity rather than using similar terminology interchangeably across planning and reporting.
Hypothetical study example
In a hypothetical trial, the main finding is uncertain and the team calculates low observed power as an explanation. The statistician compares planning assumptions with the information actually obtained. The report presents the estimate and compatible effects instead of relying on one retrospectively calculated number to explain the entire outcome.
Design review checks
- Retain the effect and variability assumptions used in the original power calculation.
- Explain data losses when comparing realised information with the planned information.
- Connect result interpretation to estimation, uncertainty and clinical relevance.
Record the decision and its limits
Accepted assessment does not automatically label every uncertain finding a low-power problem. Justify further research through clinical importance and remaining uncertainty. Do not present a post-result calculation as fresh confirmatory evidence. Report study strengths and limitations without converting lack of significance into a certain claim of no effect or a certain claim of inadequate design.
Frequently asked questions
- Does observed power alone explain uncertainty?
- No. Estimates and intervals provide more direct interpretive information.
- Is every nonsignificant study inadequate?
- That conclusion is not automatic; consider design, information and the clinical question together.