Dear Maurizio:
On Mon, Jan 4, 2010 at 8:41 AM, Maurizio La Rocca <[email protected]>
wrote:
I have a crucial doubt about the weights to use in a meta-regression.
For fixed-effect I have to use this Stata command: vwls Y(effect size)
DummyX1 DummyX2. Sd(StandardErrorEffectSize)
For fixed-effect I have to use this Stata command, using reml- residual
maximum likelihood - as option: metareg Y(effect size) DummyX1 DummyX2,
wsse(StandardErrorEffectSize) bsest(reml)
My doubt concerns the weight.
If I compute a variance-weighted least squared regression do I have to
input
in the stata command the Standard Error of the Effect Size or the
inverted
squared standard error?
End running a metareg (random-effect), is it correct, in this case, the
use
of the Standard Error of the Effect Size?
You have the command syntax right: -vwls- and -metareg- take the
standard error as argument to the sd() and wsse() options
respectively. (Note that Stata is case-sensitive so it may object if
you type "Sd" rather than "sd".)
Moreover, I have a second doubt.
Please, does anybody of you know how to compute R^2 after a
variance-weighted least squared regression? Is it possible to compute it?
The current version of -metareg- includes in the output an "adjusted
R-squared" value that is computed as the percentage reduction in the
(residual) between-study variance when covariates are fitted (compared
to the random-effects meta-analysis model with no covariates). To
install the latest version of -metareg- type "findit metareg" in Stata
and click on the link labelled "sbe23_1", which is currently the fifth
item down (at least in Stata 11 with the latest updates installed). Or
if that doesn't work for you, try "net sj 8-4 sbe23_1". For further
discussion of the updated version of -metareg- see:
Harbord RM, Higgins JPT. Meta-regression in Stata. Stata Journal 2008;
8(4):493-519. <http://www.stata-journal.com/article.html?article=sbe23_1>
Regards,
Roger.
--
Roger Harbord
http://www.epi.bris.ac.uk/staff/rharbord.htm
