***** To join INSNA, visit http://www.insna.org ***** Hello everyone, I am a PhD Candidate working on my thesis in the Faculty of Information & Media Studies at the University of Western Ontario who has lurked on this list for a while now. Now I have a question I hope you can help me with. I am working with social network data for a project focused on networks for information and help related to HIV/AIDS in rural Canada. We have data for three regions of Canada. Network participants include people living with HIV/AIDS, their friends/family members, their health care providers and service providers. We sampled this network using recruitment through health and social service agency partners, followed by snowball methods based on nominations. In so doing, we relied on a sampling approach set out by Goodman (1961). We conducted semi-structured interviews with participants in each of these categories in order to elicit information about their networks and how these networks work. We chose to conduct interviews only with people who lived in our rural regions of interest, or who were located in the closest urban centres but worked with a number of our participants from these rural regions. However, we documented out-of-region nodes without pursuing interviews with them. From this, a list of networks for HIV/AIDS-related information/help/support were created for each participant, and we have worked to construct whole network data from these interviews by identifying interconnections between participants based on these multiple interviews. A problem has arisen, though, in that we initially hoped to be able to speak with all key participants in these networks, but fewer people participated than we'd hoped - and in one area, we are missing some key players mentioned by multiple participants as members of their networks. We have 117 participants from the three regions who participated in semi-structured interviews, but this represents a small proportion of the people mentioned in interviews. Can anyone suggest an approach to dealing with this missing data so I can extrapolate/model the whole network? I very much want to use whole networks as my unit of analysis and whole network metrics (such as density and fragmentation) to compare these networks as I think this is a particularly rich area of my data. In the Wasserman & Faust text, I have found citations to Frank (1971)'s work on this problem, but I'm wondering if any more recent approaches for this have been developed and whether any SNA software programs (such as UCINET, which I am currently using) can accommodate these calculations. Thank you very much for your help in advance. Regards, Tiffany Veinot, BA, MLS PhD Candidate Rural HIV/AIDS Information Networks Study Project Coordinator Faculty of Information and Media Studies The University of Western Ontario E-mail: [log in to unmask] Voice: 416-698-7743 Visit my Academic Profile at: http://www.fims.uwo.ca/whoswho/facultypage.htm?PeopleId=119595 _____________________________________________________________________ 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.