This is a summary of how I want to analyze my data. I want assistance on how to use Statnet, ergm and meta-analytical techniques in R to analyze social networks of family ties, ethnic ties and religious ties on firm growth in 264 business organizations. The interactions between organizational members were mapped into family, ethnic and religious ties in a relational matrix in which the value of a cell (ij) was coded as 1 when an employee i and j report mutual interaction and 0 otherwise. This was done for each of the firms. A social network was assumed for mutual interactions. I have already drawn the relational matrices of family, ethnic and religious ties for each firm on an excel sheet. The next step is to use Statnet, ergm and meta-analytical techniques in R to generate the parameters/estimates of the family, ethnic and religious networks in each firm and subsequently examine their effects on firm growth.
That's a grander question than we can usually address here. More often, we are helping using reproducible examples, called a reprex to troubleshoot specific problems. The question might even be over-broad for the
statnet.org mailing list.
I can only offer some general observations.
The first is that it appears that you have the same initial analysis to do 264 times--creating a social network object, called a
graph (not to be confused with a chart; this one is a mathematical object). Even though you may eventually want to compare the companies on graph measures of centrality, connectedness, etc., this is where you start.
nodes in each graph. Interactions between employees are
edges and the types of interactions are edge
attributes. The graph objects may either be unidirectional, birectional or multi-directional.
For an illustration of how such graphs are constructed, my unpublished paper illustrates some of the tools involved and might get you started.