I have two correlation coefficients (r1 and r2), obtained within the same sample (20 subjects). My aim is to test it they are significantly different.

r1 is the correlation between a neurophysiological parameter and a behavioural parameter in condition A; r2 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.

My questions:

1) Does this procedure seem reasonable to achieve my purpose? (test if r1 and r2 are significantly different);

2) There is a way to decide the number of iterations, or is it totally arbitrary? (for example..I can go with 1000?).

Thanks in advance,

Simone