I am calculating Spearman correlations multiple times between individual data vectors that are not necessarily of the same length. So for example,
X1=[1,2,3], Y1=[2,3,1] and
X2=[10,2,3,4,5], Y2=[2,3,1,1,1], correlating
Y2. I now want to retrieve an average correlation coefficient.
I am aware that a common approach is a Fisher transformation on the individual coefficients; averaging the transformed values; and a back transformation.
However, I have two issues:
Some of my correlation coefficients are 1 where the Fisher transformation is not defined. Is there some common way of handling that case?
Do I need to cope somehow with the different vector lengths? I found some short information about that in the following paper, but wonder whether this is necessary or there is another approach.