***** To join INSNA, visit http://www.insna.org ***** Since degrees distributions in networks are heavy tailed and are thus not normally distributed and is it still ok to correlate them using some correlation measure like pearsons r? Is it robust enough? Lets say we have a network that notes friendships, and a network that notes the actually exchanged information. So a hypothesis could be that persons with a high amount of friends also exchange a lot of information. For that I would correlate the degrees of those two networks. Would that be a valid approach? P.S. I've found a paper on arxiv on this, maybe you know of more: http://arxiv.org/pdf/1003.1634.pdf I also remember hearing something about the QAP correlation ( http://faculty.ucr.edu/~hanneman/nettext/C18_Statistics.html) method, but i think it was for the case when both network measures come from the same network. _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.