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I am a PhD student working with information ego-networks collected within a place-based community.  I was hoping to elicit some suggestions for how to go about using p*/EGRM techniques to analyze these ego-networks.  The data we have derived is only partially observed in that we have ego's ties to alters and alter's ties to alters, but only withn the boundaries of each individual ego-network.  We do not have any information regarding the ties across ego-networks. Also, in that this data was collected in a place-based community, we do not have clear boundaries for what constitutes the complete network (i.e., we don't have a master list of all the residents), which means we do not know precisely what tie we do not have data for, which makes some of Handcock and Giles work on adjusting for known missing data less applicable to our situation (I think). 

As of now I'm thinking one way to apply ERGM techniques to this dataset is to simply treat all 218 of our ego-networks as individual complete networks and analyze them as such.  Then do some kind of meta-analysis across the 218 ego-networks to glean some patterns and trends.  Another option might be to put all 218 ego-networks into a single matrix, comprised of all our respondents and all the people sources they named, and control for the mutual exclusiveness between each ego-network  by giving "0" values to all the potential relationships outside the confines of each ego-network.  The problem with this is that in this tight community we have reason to believe that mutually exclusivity cannot be assumed in that some alters were coincidentally named by more than one ego.  But this type of data was not systematically built into our survey design.

Any feedback would be welcome.  I look forward to your responses.

Lindsay Young
Doctoral Student
Northwestern University
School of Communication
Media, Technology and Society (MTS)
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