I have two correlation coefficients ($r_1$ and $r_2$), obtained within the same sample (20 subjects). My aim is to test it they are significantly different. $r_1$ is the correlation between a neurophysiological parameter and a behavioural parameter in condition A; $r_2$ is the correlation between the same neurophysiological parameter and the same behavioural parameter in condition B.
I was thinking to apply a bootstrap procedure for each condition, in order to obtain two distributions of correlations. Then, I can simply run a two-sample t-test, to test for a significant difference.
- Does this procedure seem reasonable to achieve my purpose? (test if $r_1$ and $r_2$ are significantly different)
- Is there a way to decide the number of iterations, or is it totally arbitrary? (for example..Can I go with 1000?)