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I recommend two options.  The easiest approach is to use ORA, which was really designed for meta-networks (multiple types of links and multiple types of nodes).  This has some great visualization features, plus it is easy to visualize changing network effects by turning types of links on or off.  ORA can import from many different formats.

For the statistical analysis, I recommend the statnet package in R.  Mark Handcock has a tutorial from Sunbelt floating around the web somewhere that is really easy to follow.  Plus the guys who manage statnet are very helpful and supportive.  The command you would use is ergm, which is essentially logistic regression for the presence of a tie.  You can include structural terms as well as node attributes as factors in the model.  The nodecov term is for the node attribute factors.  If you want to learn more about ergms, I recommend a sage book by Knoke and Yang.  They have a short easy to follow explanation at the end and the book is pretty inexpensive.

I do a lot of applied multiplex stuff, so let me know if you need help.

Ian

Ian McCulloh, PhD
Major, US Army
Assistant Professor
US Military Academy
West Point, NY 10996  
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-----Original Message-----
From:         Daniele Mascia <[log in to unmask]>
Date:         Sat, 23 Jan 2010 19:53:34 
To: <[log in to unmask]>
Subject: [SOCNET] multiplexity

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Hi Socnetters,
  
 I am performing a social network analysis on
a community of approximately 200 physicians. In particular, I collected
data concerning two distinct kind of social relationships among medical
doctors: professional interaction and co-authorship. For each clinician, I
also collected attributional data such as age, tenure, specialization,
formal affiliation to hospital structures, utilization of evidence-based
knowledge etc. One of my objectives is to study whether attributive
features of individuals are associated with both kind of network ties,
distinctively and jointly. 
 
I am
wondering if anyone has had experience with software for the joint
analysis of multiple set of relationships. Any help or references to
articles where researchers dealt with this kind of analysis (multiplexity)
are highly appreciated.
 
Thank you in advance for your
help!
 
Regards
 
Daniele

Assistant Professor of Health Care
Management
Department of Public Health
Catholic U. Rome (IT)

 



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