I was asked this question about the demonstration of power.
There are two groups of data, say control and treatment. If conducting a test( say a linear regression including other factors, but the response variable was log-transformed before entering the regression), the results shows no significant difference between the control and the treatment group.
A colleague manipulated the data by dividing all treatment outcome variable by 2, then doing the same analysis and now there is significant difference between the two groups. Then he argued that if the treatment group data was lower by a factor of 2, this method could have identified the difference. And this shows the power of the analysis or of the test.
I do think there is nothing wrong with this as a way to demonstrate a what would be case. But I feel it is odd to manipulate data to show the power. It is conceptually similar to minimum detectable difference, but the manipulation ignored other factors by treating all the y's from the treatment group in the same way. Of course if you shift all the data in the same direction far enough with respect to the sample size, then the difference would have been identified as significant.
Is this a real added value to the analysis and worth of some space in a journal publication?