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st: RE: meta-analysis residual question


From   "Garrard, Wendy M." <wendy.garrard@vanderbilt.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: meta-analysis residual question
Date   Fri, 18 Feb 2005 09:48:01 -0600

Thanks very much to Roger Harbord who kindly pointed out my "operator
error" in using [generate] to produce the predicted values with the
regression equation. 

Since it may be helpful to others new to using Stata and the
postestimation regression commands, I will admit to the nature of my
fundamental error. When calling the regression coefficients, I should
not have used the "minus" sign in my equation, as Stata was already
providing negative coefficients where appropriate--I should use all "+"
signs in applying the regression equation and let Stata take care of the
rest.

Regards,
wg


Regards,
wg
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Garrard,
Wendy M.
Sent: Thursday, February 17, 2005 9:55 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: meta-analysis residual question

Could someone help me understand the fitted values that are generated
post-estimation using the metareg (updated version)?

After a meta-regression I generated the fitted values using (predict
yhat).

But, I get quite different values when I use the regression equation to
obtain the fitted values like so:
	(gen yhat2 = _b[_cons] + _b[Var1]*Var1 + _b[Var2]*Var2 -
_b[Var3]*Var3)

For example, for the first record in my data set, the fitted value is .5
using the predict command, and 1.1 obtained via the equation.

I assume this difference has something to do with how the weighting is
used in the postestimation command, but I'd like to understand how to
correctly approximate the fitted values using the equation.

Thanks,
Wendy Garrard
Vanderbilt University

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