Dear Dr. Mehta,
I have been exploring the xxM package and am excited by its capabilities.
One capability that I noted in descriptions and that particularly important to me is the ability to capture multiple group membership. However, I could not find a reference to how to implement it in tutorials.
A brief description of my data and what I am trying to accomplish:
It is a 3-level dataset, level 1 being employees, level 2 being team leaders, and level 3 being executives. Employees are nested within teams/team leaders. Team leaders are/ can be connected to executives. Some have one connection/affiliation, some have multiple, some have none. This is where the multiple membership issue comes in.
In terms of model, what I am trying to do is to predict an outcome at the employee level by an attribute of the executives. In principle, this is very similar to the example 8 in the tutorial (school resources -> teacher intercept -> student outcomes), with the difference being that my level 2 units are neither nested nor fully crossed, but have between 0 and x affiliations/connections with the level 3 units.
I would be very grateful for any guidance you can provide or any material you can point me to that has an example of how to implement the multiple membership structure.
Kind regards,
Julija