is a service of INSNA, the professional association for social
network researchers (
Can any of you provide me with a few good papers on
handling missing data in network studies? Specifically, if
I'm studying collaboration and some subject opts out of the
research, or if I'm conducting weekly surveys and some
respondents fail to complete a survey for a given week or we
choose to skip certain respondents in certain weeks to reduce
burden on the subject. I'm also looking for a possible power
analysis for these research decisions/situations.
For the project, subjects will be evaluated in their
current office configuration, then moved to an open plan,
designed for greater collaboration. There are several sources
of network data that I will collect. I will have billing
data, which ties subjects to projects that they work on
(co-project network). I will have access to email meta-data
(email network). And I will be able to survey subjects on
It does not appear that I will be able to survey all
respondents each week. The project lead has asked me about
power analysis to quantify the effect of missing respondents.
In other words, how many people do I need to survey to have
useful network data.
I have explained ergodicity to my research team and how
inference can be a problem, given the dependent nature of
networks. I don't really need any more info on that angle.
What I would appreciate is any papers that discuss the
statistical effect of missing data in an ergm, stochastic
actor-oriented model, or basic SNA.
As I recall, similar questions have been raised on this
forum before. I'm sorry I couldn't locate those posts.
I'd also be interested in any papers on similar studies
focused on increasing collaboration and innovation through
office space design. I'm already familiar with Kerstin
Sailer's excellent work in this area, but would be interested
in other efforts.
Ian McCulloh, Ph.D.
Johns Hopkins University