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Re: st: Advice on xtmixed specification,pre/post two-group design


From   "Clyde Schechter" <clyde.schechter@einstein.yu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Advice on xtmixed specification,pre/post two-group design
Date   Wed, 27 Jul 2011 07:10:26 -0700

I can suggest a couple of things to look into:

xtmixed score_change female urm english control time#control || tch_id:
control, cov(unstruct) || id: , mle

seems mis-specified.  In particular, if your dependent variable is
score_change, I don't think there should be any reference to time in the
independent variables.  In fact, with score_change as the dependent
variable, in your data there should be only a single observation
corresponding to the pre-post pair of observations in the original data. 
So either you are analyzing largely duplicated observations, or if you
have reduced to one observation per pre-post pair (you don't say whether
or how)  whatever value time takes on in these observations is
meaningless.  Either way, you wouldn't expect to see a time#control
effect.

I think if you take time#control out of the model and just focus on the
control coefficient you will get what you are looking for.

Other things to bear in mind: most of the time a model with change score
as dependent variable will give you more or less the same results as a
model with separate observations at each time and within-pair clustering
accounted for.  But, if there is a substantial amount of missing data on
the score variable, you may find that the sample analyzed in the change
score variable is a noticeably smaller, and probably biased, subset of the
cases included in the analysis relying on separate pre and post
observations.

Hope this helps.


Clyde Schechter
Department of Family & Social Medicine
Albert Einstein College of Medicine
Bronx, NY, USA

Please note new e-mail address: clyde.schechter@einstein.yu.edu

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