The Reviewer Asked: Justify Your Sample Size

First establish what actually happened

A reviewer asking for sample-size justification may be asking for missing assumptions, a feasibility explanation, or an account of what the available sample can support. These are different requests.

Locate the original protocol and calculation, if one exists. Record its date, primary outcome, effect assumption, variability or baseline risk, significance level, power, allocation, and loss allowance. Check that these describe the design that was implemented.

When the sample was fixed

A retrospective study may include all eligible records over a specified period. Explain the period, eligibility process, and practical constraints honestly. Do not create a calculation after seeing the results and present it as the reason the sample was chosen.

For example, a fictional study might have included every eligible admission in a predefined two-year window. Its revised Methods could explain that sampling frame, while the Results and Discussion describe the precision of estimates and the limitations of sparse outcomes. This is an explanation of the design, not proof that the sample is adequate for every proposed model.

Prepare the response in three parts

1. State the actual basis for the sample.
2. Identify the new information added to the manuscript and its location.
3. Explain the remaining limitation and any justified analysis changes.

Avoid treating a non-significant result as evidence that an effect is absent. An uncertainty interval provides more information about the effects compatible with the data and model than an isolated threshold decision.

Use the precision explorer for a single-proportion planning illustration. Its scope does not include regression-model adequacy or clustered designs.

Download a reviewer response tracker, or open the Reviewer Comment Decoder. Statistical revision support can help when new analysis is needed.

Further reading: Cochrane on interpreting statistical results.