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 at r-project.org] On Behalf Of Lukas Dylewski
Sent: Saturday, 13 April, 2019 19:53
To: r-sig-meta-analysis at 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
--
?ukasz Dylewski, M. Sc.
PhD Student
Department of Zoology, Institute of Zoology
Pozna? University of Life Sciences
Wojska Polskiego 71C
60-625 Pozna?, Poland
http://ecology1.wixsite.com/farmlandecology