Based on the lack of responses to my previous network question, perhaps this is not quite the place to ask this question, but I'll give it a try.
I am planning a series of studies that involve small groups of people. In a typical study, the participants will meet in groups of 4 to have a discussion about a particular topic. As a group, the (student) participants will reach a decision about the topic (e.g., whether to support or oppose a proposed change in university policy). The discussion will be videotaped, and we will use transcripts of the discussion to obtain information about who is talking to whom about what topics. In addition, the participants will complete ratings of themselves and each other (e.g., What is your opinion about the proposed change? What do you think is this person's opinion of the proposed change?). I will also have a variety of data about the individual characteristics of all the participants. Thus, each group from each study will give me a 4-node network with directed, valued edges and a variety of attributes about each node. In a typical study, I might have 20 - 30 of these small groups (i.e., small, 4-node networks).
In all the studies, I will be interested in group-level, relationship-level, and individual-level outcomes. I have provided below a sampling of the kinds of questions I would want to ask from these data:
- Which groups express the most agreement in their discussions? Which groups express the most disagreement? Is group composition related to agreement / disagreement and to the final decision outcome?
- Which pairs of people like each other during the discussion? Which pairs of people dislike each other? How are the pairwise patterns of liking related to the final decision outcome?
- Who has the most influence on the course of the discussion? Who has influence over the final decision of each group? Are there any individual difference characteristics that are related to influence over the discussion and / or final decision?
And so on. What I am looking is the proper statistical model to use to investigate samples of networks, rather than individual networks.
I have read a bit about single-network methods (like exponential random graph models, for which there is a nice R package available), but these methods do not seem appropriate, since I am dealing with a set of independent networks, rather than a single network. In addition, a plain linear mixed model does not seem appropriate because I am collecting explicitly relational data. Finally, although a method like the social relations model seems appropriate for this situation at first blush, the social relations model seems to only partition the variance in round-robin ratings into perceiver, target, and relationship sources rather than allowing me to, for example, relate the patterns within a set of networks to overall network outcomes.
Could anyone offer some advice about which statistical model might be appropriate for my situation? Any readings suggestions and / or software recommendations would be greatly appreciated. (FYI, I am a proficient R user, so R package recommendations would be especially appreciated).
At the request of Alex Williams, I have posted some example data here in csv format to give everyone a concrete example of the type of data I'm working with. In the sample data, participants, identified by
participant_id, are each in 4-person groups, identified by
group_id. The participants discuss a proposal and decide as a group whether the support or oppose the proposal.
group_decision is the result of the group discussion. The participants also rate their own attitude toward the proposal (
pers_att), their perceptions of the attitudes of the other group members (
person_id tracks who
p4 are within each group), and their own enjoyment of the discussion.
In the sample data, I might be interested in the following sorts of questions:
- Are personal attitudes related to group-level decisions?
- Are personal attitudes related to personal enjoyment of the group discussion?
- Were people accurate in their ratings of other peoples' attitudes?
- Were the ratings of others related to others' enjoyment of the discussion?
- Does disagreement within a group (quantified, for example, by the difference between the minimum and maximum attitude ratings) relate to group-level decisions?
- Does disagreement within a group cause people to enjoy the discussion less?
- Did people who enjoyed the discussion more have more influence over the outcome?