[R-meta] overall effect size
Viechtbauer, Wolfgang (SP)
wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Tue Apr 30 20:42:25 CEST 2019
Dear Lukas,
You could use the predict() function to compute the predicted average effect for a each level of 'status' when fixing 'logmass' to the mean of this moderator. The predict() function will also give you the SE. It will be something like:
predict(res1, newmods = c())
but without the output from res1, I cannot tell you what needs to go inside the c().
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Lukas Dylewski
Sent: Saturday, 13 April, 2019 19:53
To: r-sig-meta-analysis using r-project.org
Subject: [R-meta] overall effect size
Dear Wolfgang ,
I am working with a meta-analysis in R (metafor package) using a mixed
model framework to examine experimental effects of rodent seed predation on
plant recruitment as a function of various plant species characteristics. I
decided to go with metafor given that this allowed to account for random
factors (specifically the study source, each of which typically estimated
effects for multiple species) while testing for the influence of multiple
fixed factors in the same model.
The one snag I’ve hit concerns deriving estimates of the mean effect size
(the response) for my two classes of “status” (native or exotic) while
accounting for the values of the continuous covariate “logmass.” From
playing with another meta-analysis package (OpenMEE, an interface that
relies on the R package meta.analysis, which does not allow the addition of
random factors).
How I can estimate the mean effect size for "status" (alien and native)
representative logmass values? Can I use the equation? But I’m unclear how
I would calculate the associated SE for each estimate. Could the solution
possibly be as easy as a simple equation that you already have??
The models look like:
res1 <- rma.mv(yi, vi, mods = ~ logmass + I(logmass^2)+ factor(status) +
logmass:factor(status), random=~1|pub,data=metaan, method="REML")
Best
Lukasz
--
Łukasz Dylewski, M. Sc.
PhD Student
Department of Zoology, Institute of Zoology
Poznań University of Life Sciences
Wojska Polskiego 71C
60-625 Poznań, Poland
http://ecology1.wixsite.com/farmlandecology
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