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st: Use of margins command to get individual level predictions but where one factor is treated as balanced


From   Sam Brilleman <sam.brilleman@bristol.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Use of margins command to get individual level predictions but where one factor is treated as balanced
Date   Thu, 04 Aug 2011 14:00:44 +0100

Hi STATAlisters,

I am hoping someone can help me with getting the correct -margins- syntax. I have found several people with similar questions, but no clear answers.

I have a GLM (log link) model fit using the following command:

glm totalcost_modelfit i.practiceid i.age_gender i.imd_decile i.QOF_MMscore_trunc6, link(log) family(gamma) eform

There are 174 levels for the i.practiceid factor variable. I wish to calculate the marginal mean for the outcome variable (totalcost_modelfit) within each practice, whilst treating the practice effect as balanced (i.e. using the average practice effect for the full sample). I've tried:

margins, over(practiceid) at((asbalanced) practiceid)

but this obviously treats practiceid as balanced within each practice rather than across the whole sample, so I may aswell have just used -predict- and calculated the mean predictions by practice manually. And if I try:

margins practiceid, at((asbalanced) practiceid)

then individuals from the full sample are contributing to the estimated marginal mean for each practice aren't that? I don't really want that since the age-gender distribution may differ across practices.

Ideally I would want to -predict- individual level prediction but where I am allowed to treat the practice effect as balanced (i.e. use the average practice fixed effect) and then I would just calculate the mean prediction within each practice manually (NB this would give me more flexibility as I would have the individual level predictions available too). Possibly using the -adjust- command? However it says that margins has superseded this.


Thanks for any help,
Sam.

------------------------------
Sam Brilleman
School of Social and Community Medicine
University of Bristol
Canynge Hall
39 Whatley Road
Bristol BS8 2PS

Tel: (0117) 928 7319
Email: sam.brilleman@bristol.ac.uk
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