***** To join INSNA, visit http://www.sfu.ca/~insna/ ***** I have a question on elementwise correlations between the entries in each of two matrices. My data: I have complete network data for two cities at three points in time. Data are from board interlocks. I have decomposed these six networks in two relational networks. One relation I am defining as economic and the other as civic. I want to measure the overlap between the two networks at any given moment in time (I am not trying to compare across time so the actors in both networks are identical). Specifically, I am asking, at the level of ego, to what degree are actors connected along one relation also connected on the other? And, for the network as a whole, to what degree does one network overlap with the other? I am calling the concept I am trying to measure 'multiplex independence.' The idea is that a person's network is perfectly 'multiplex independent' if their ties on one relational dimension (civic) do not overlap with any of their ties on another relational dimension (economic). Similarly, a complete network is 'multiplex independent' if actors' ties on one relation do not overlap at all with those same actors ties on another dimension. I have looked at the QAP proceedure. That gets me partially there since it tells me whether the overall structures of the networks are similar with some statistical confidence. But, it doesn't tell me much about the degree to which specific ties in the each of the two networks do or do not overlap. I have also looked at Burt's measure of structural holes which is related. However, its not clear to me how it plays out in multi-relational space (I don't think that's covered in the book). Someone at some point must have thought about this before me. But I have looked through Wasserman and Faust and a few recent papers on comparing networks and I haven't been able to find anything that is doing exactly what I need it to do. Any directions you can point me that are more specific than QAP? Thanks. Sean _________________________ Sean Safford Ph.D. Candidate MIT Sloan School of Management - Institute for Work and Employment Research - Industrial Performance Center 50 Memorial Drive, Suite 580 Cambridge, MA 02142 617 258 9728 [log in to unmask] www.mit.edu/~ssafford _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.sfu.ca/~insna/). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.