How does sample size influence standard error, and what implications does this have for research editors assessing study methodology?

Standard error is inversely proportional to the square root of the sample size. This means that as the sample size increases, the standard error decreases, indicating a more precise estimate of the population parameter. For research editors, this is critical: they evaluate whether the sample size is adequate to achieve a sufficiently precise estimate (i.e., a acceptably small SE) for the study's objectives. A very large SE can suggest an underpowered study or high data variability, potentially leading to imprecise or non-generalizable findings. Editors expect authors to justify their sample size, often in relation to the desired precision indicated by the SE, to ensure the study's methodological soundness.