st: xtmixed: variation at the highest level

[Peter Goff <peter.t.goff@vanderbilt.edu>]

I have a question that pertains to one of the examples given in the  
xtmixed help file. Using the two-level data set "webuse nlswork" from  
the first example in the help file, I see that the command:
xtmixed ln_w grade age c.age#c.age ttl_exp tenure c.tenure#c.tenure ||  
id: grade, cov(unstruct)
can be used to create a random coefficient model. However, the data  
file itself shows that the variable grade does not vary at the highest  
level (level 2), i.e. it is constant within id (level 1).

From a multi-level modeling approach I have interpreted random  
coefficient models to mean that the slope (of grade, in this example)  
for each cluster can have a different impact upon the dependent  
variable (ln_w, here). Although within this context there is no  
variation of grade within individuals so I'm not clear how to  
interpret this model.

Taking this a step further, if the model included an interaction  
between the level 2 variable and a level 1 variable such as:
xtmixed ln_w grade c.grade#c.age age c.age#c.age ttl_exp tenure  
c.tenure#c.tenure || id: grade, cov(unstruct)
would this change the interpretation of the random component of grade?

Kind thanks,
~Peter

Peter Trabert Goff
PhD student
Department of Leadership, Policy, and Organizations
Vanderbilt University

Peabody #514
230 Appleton Place
Nashville, TN 37203-5721
Tel. 615-415-7844
Fax. 615-322-6596
peter.t.goff@vanderbilt.edu




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