If the power level is low, it may be an explanation to the non-significant result. Actually, even if power is .01, a researcher can still correctly reject the null one out of one hundred times. P. When power is insufficient but increasing sample size is not an option, you can make up subjects. It is a legitimate and ethical procedure. A resampling technique named bootstrapping can be employed to create a larger virtual population by duplicating existing subjects.
Analysis is conducted with simulated subjects drawn from the virtual population.
Resampling procedures will be discussed in another section. Last but not least, low power does not necessarily make your study a poor one if you found a significant difference. Yes, even if the null is rejected, the power may still be low. But this can be interpreted as a strength rather than as a weakness. Power is the probability of detecting a true difference.