Dear Wolfgang,
Thank you very much for the quick reply. I already assumed that it might
get too complicated,
so I will just stick to using a moderator (as you also suggested).
Best,
Anke
On 24.05.2012 17:05, Viechtbauer Wolfgang (STAT) wrote:
At the moment, there is no possibility of specifying the weights with the rma()
function. While the main model fitting part could be easily adapted to
incorporate user-specified weights, the problem comes in with all the
additional statistics that can be computed based on a fitted model. How should
the predict() function now work? What would be the definition of I^2 now? How
would one generalize the influence and outlier statistics to that case? Just to
give some examples.
Of course, I could leave out such things when the user has specified the weights, but
then things also get confusing for the user. For example, it is already less than ideal
that you can only use the trim and fill method with models that do not incorporate
moderators. Nobody has (as of yet) generalized the trim and fill method to that case. But
when there are too many "special cases", the package becomes unusable.
I did consider user-specified weights at one point, but it opened up so many
cans of worms that I preferred to quickly put the lid pack on those cans. That
item is written down in my to-do list, but to be honest, it is somewhere at the
very end of that list.
If you are hesitant to combine the results from those two types of studies,
what about simply using a moderator to distinguish the two groups?
Best,
Wolfgang
--
Wolfgang Viechtbauer, Ph.D., Statistician
Department of Psychiatry and Psychology
School for Mental Health and Neuroscience
Faculty of Health, Medicine, and Life Sciences
Maastricht University, P.O. Box 616 (VIJV1)
6200 MD Maastricht, The Netherlands
+31 (43) 388-4170 | http://www.wvbauer.com
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On Behalf Of Anke Stein
Sent: Thursday, May 24, 2012 15:59
To: r-help@r-project.org
Subject: [R] package metafor: specify weights?
Dear R-experts,
Dear Wolfgang,
Weighted model fitting in metafor uses the inverse of the study specific
variances as weights.
I am wondering if it is possible to specify different weights.
In my meta-analysis, there are two types of studies with (intrinsic)
differences in their range of sample sizes (which are used to calculate
the variances of Fisher's z).
I would like to try normalizing the sample sizes within each set of the
two study types and use these normalized sample sizes as weights.
Would that be possible with rma()? So far, I only found the option
"weighted = TRUE/FALSE", but no possibility to specify which weights
should be used.
Many thanks in advance,
Anke
--
__________________________________________________________
Anke Stein (Dipl.-Biol.)
Biodiversity, Macroecology& Conservation Biogeography Head Prof. Dr.
Holger Kreft Georg-August University of Göttingen Büsgenweg 2 | 37077
Göttingen | Germany
phone +49(0)551-39-13761
fax +49(0)551-39-3618
ast...@uni-goettingen.de
http://www.uni-goettingen.de/biodiversity
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