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st: xtmixed: variation at the highest level


From   Peter Goff <peter.t.goff@vanderbilt.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: xtmixed: variation at the highest level
Date   Mon, 8 Feb 2010 17:47:04 -0600

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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