Hello,
Great to see the new metafor package for meta-analysis.
I would like to perform a meta-analysis in which I initially calculate the
intercept of the model with a nested random-effects structure. In lme, this
would be
model<- lme(v3~1, random=~1|species/study, weights = varFixed(~Wt), method =
"REML")
where multiple effects sizes are measured for some studies and more than one
study exists for some species. I would like to treat species as a random
effect rather than a fixed effect if possible. I understand that lme will not
give me the correct weighted answer (something to do with not being able to fix
the variances at the lowest level?) so that I should use metafor.
However, I only see that metafor accepts moderators and I'm assuming that they
are treated as non-nested fixed factors, if for example I used:
x<-cbind(species,study)
rma.uni(yi=v3,sei=vi,mods=x, method="REML")
Am I correct in thinking that I cannot obtain the correct weighted random
effects intercept using lme?
How can I obtain a weighted purely random-effects model with nested factors
using metafor or have I misinterpreted something from the metafor manual?
Thanks,
Mark
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