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st: RE: prediction after y-logged regression


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: prediction after y-logged regression
Date   Mon, 2 Jun 2008 13:29:24 +0100

There is a large literature on this problem, especially it seems in
health economics. 

If you use -glm, link(log)- the predictions are in essence adjusted
automatically. 

What you describe is a special case of smearing, which is very easy too
in the case of log transformation. In my experience the results of using
-glm, link(log)- and of smearing are very similar. I prefer -glm-. 

Nick 
n.j.cox@durham.ac.uk 

Shehzad Ali

I am running a regression in which y variable is logged
(semi-logarithmic). 
The literature suggests that in order to get an anti-logged prediction
of 
yhat, one should proceed like this:

1. Run the regression and predict yhat,

2. Then exponentiate the predicted yhat, and finally

3. Mutiply the exponentiated predicted yhat by the mean value of
residuals 
from the regression (otherwise known as smearing).

I was wondering if there is a direct way to do it in stata or if there
is 
any other method that experts would suggest to get anti-logged
prediction.

Thank you,

Shehzad

-- 
Shehzad I Ali
Department of Social Policy & Social Work
University of York
YO10 5NG
+44 (0) 773-813-0094
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