Hi everyone!

I have a question about detecting multivariate outliers in a correlation analysis. I'm calculating Spearman correlations between 5 variables (in a within-subject design), and I was suggested to calculate Mahalanobis distance for all 5 variables for detecting multivariate outliers. However, each correlation is a two-dimensional space, so it might have different outliers with respect to the initial five-dimensional space, if I understand correctly. But detecting outliers for each correlation separately also doesn't seem like a good idea.
Could someone please clarify this? Thanks!