Hi,
I'm using metafor to perform a mixed-effects meta-analysis. I'd like to
test whether the effect is different for animals and plants/whether "group"
(animal/plant) influences the effect size, but am having trouble
interpreting the results I get. I've read previous posts about QM in
metafor, but I'm still a bit confused. I've dummy-coded the factors:
MData$k.animal<-ifelse(MData$Type=="Animal",1,0)MData$k.plant<-ifelse(MData$Type=="Plant",
1,0)
I've then run the model with the following script:
MixModel<-rma(z, v.z., mods=cbind(k.animal, k.plant), intercept=FALSE,
data=MData, subset=(Response=="Tolerance"))MixModel
I receive the output:
Test of Moderators (coefficient(s) 1,2):
QM(df = 2) = 8.5758, p-val = 0.0137
Model Results:
estimate se zval pval ci.lb ci.ub
k.animal 0.4877 0.2703 1.8042 0.0712 -0.0421 1.0175 .
k.plant 0.5095 0.2209 2.3066 0.0211 0.0766 0.9424 *
Does this mean that, overall, there is a significant effect of "group" on
the overall effect size (based on the QM test)? If I want to test whether
the effect size for plants is different to that for animals, can I use:
MixModel2<-rma(z, v.z., mods=cbind(k.plant), data=MData,
subset=(Response=="Tolerance")) ?
Here I get:
Test of Moderators (coefficient(s) 2):
QM(df = 1) = 0.0039, p-val = 0.9502
Model Results:
estimate se zval pval ci.lb ci.ub
intrcpt 0.4877 0.2703 1.8042 0.0712 -0.0421 1.0175 .
k.plant 0.0218 0.3491 0.0624 0.9502 -0.6624 0.7060
Does this mean that there is no significant difference in effect size
between plants and animals (now the intercept?) ? Or is this something
completely different?
I'd really appreciate any input,
Rachel Slatyer
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