I have a large data set where employees (level-1) are clustered within agencies (level-2). A majority of the employees have worked in multiple agencies (i.e., employees are nested within more than 1 agency). Two questions...can MPlus handle a multiple membership model such as this. If not, is there a procedure in MPlus that would allow me to create a variable to sum the number of agencies that an employee works in so that I can treat this as a fixed effect. For example, if a participant has data that looks like the following:
agencyid employeeid 1 1 1 1 2 1 2 1
Because this employee worked in 2 agencies I would like to be able to create a variable that would return a value of 2, since this employee worked in 2 agencies. Thank you!
Hi, I looked at the TYPE = CROSSCLASSIFIED syntax in the handout and could not see any examples in which weights are applied to reflect the relative contribution of different groups in a multiple membership model. I have students nested in teachers with some students having multiple teachers or having changed teachers across the considered time period. I don't want that all teachers are given equal weight but that those who taught students for longer receive more weight. Can I do this in Mplus? Thanks.