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I am troubling by the same issue. I found the paper of
Stoke,D.and Richards, W.D. (1992) Nonrespondents in Communication Network
Studies: Problems and Possibilities. Group and Organization Management,
17(2), 193-209 very useful.
It stimulates me to think of the best way to deal with my own situation.
I ask 11 actors their frequency of contact in current construction stage and
also recall their memory in design stage but I have many missing data in
desgin stage due to the rotation of staff. I come up with the solution that
I symetricize the communication data with maximum ties to mininize missing
data. Since I decide the scale of frequency of contact to be likert scale ,1
to 5 with 1= Very infrequent and 5= Very Frequent. I treat
non-respondents,and no contact as missing data without separation.
Hope this also stimulates your thinking.
----- Original Message -----
From: <[log in to unmask]>
To: <[log in to unmask]>
Sent: Wednesday, October 29, 2003 1:47 AM
Subject: Follow up question on "Dealing with Missing Data"
> ***** To join INSNA, visit http://www.sfu.ca/~insna/ *****
> I am in the process of analyzing my data, collected on the diffusion and
> adoption of educational technologies in a higher education institution.
> research interest is focused on how the network variables affected the
> adoption of different kinds of educational technologies in an environment,
> which formally has no hierarchies (all actors have the same official
> My network consists of 98 faculty members. The response rate is: 87 % on
> the overall questionnaire and 70 % on the relational questions. Some
> actors refused to answer the relational questions (give/receive
> on educational technologies, meet on social occasions, and meet on
> professional occasions). The frequency of interactions is coded from 1-3
> (never-seldom-very often).
> I would like to get opinions from people on how to deal with different
> forms of missing data:
> How to code _and_ analyze:
> 1. Actors, who never replied to the questionnaire? (After four rounds of
> 2. Actors, who refused to answer the relational questions? (f.e. if they
> think that it is too private) Would it be ok, for example, to impute the
> missing values and then examine whether the network (including both
> responded and imputed data) affected adoption?
> 3. Actors, who were mentioned by other respondents, but left the
> organization right before or during my study and never responded.
> Do I have to treat these different categories of non-responses as missings
> or is there a way to code and analyze them differently?
> How to interpret the results?
> Thanks a lot for your input - I will of course compile the answers and
> them available to the list!
> Ines Mergel
> Doctoral Fellow
> Harvard University
> John F. Kennedy School of Government
> National Center for Digital Government
> 79 J. F. Kennedy St., T363
> Cambridge, MA 02138
> eMail: [log in to unmask]
> Office phone: 617-496 6166
> Office fax: 617-496 1722
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