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I am in the process of analyzing my data, collected on the diffusion and
adoption of educational technologies in a higher education institution. My
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 information
on educational technologies, meet on social occasions, and meet on
professional occasions). The frequency of interactions is coded from 1-3
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 make
them available to the list!
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