Report power if result is statistically significant We have submitted a paper reporting a statistically significant result.
One reviewer asks us to report what is the power to detect a significant association. As there was a previous paper on this issue, we could use the effect size of that paper to do the calculation.
However, we are surprised by this comment, and would be happy to know what is your opinion and whether you know of references that discuss calculation of power at posteriori when the result is significant.

Thank you very much for your responses.
I should have made clearer that we used a large dataset to run these analyses, so the study is unlikely to be underpowered. However, it involves a complex design, and other than running simulations, there is no simple way to compute power. We are not familiar with simulations to compute power, so I was trying to avoid this :-)

The power of the observed effect is very often equal to a simple relationship with the p-value (and the significance level) since both the p-value and the power are dependent on how many standard deviations the effect size is away from zero effect.
Let's consider this simplistic model in which you have an observation whose likelihood function can be approximated with a normal distribution. Say that the significance level is 5% (or roughly 2 deviations away from zero effect) and we observe an effect with a p-value of 1.24% (or roughly 2.5 deviations away from zero effect) then the power for that observed effect is equal to roughly 69.1% (the probability that the observed effect is more than 2 deviations away from the zero effect given that the true effect is 3 deviations away).
You have a more complex model but often the estimates are approximately equal to a normal distributed variable.

