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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