[R-meta] Question on robust multilevel meta-analysis with subgroups

[Hellen Mirr]

Hello, 
 
Apologies if this is a silly question and thank you in advance for the help as I am new to meta-analytic methods.  
I am currently planning to carry out a multilevel meta-analysis in which I have multiple effect sizes (continuous outcomes from different tasks in the same groups of participants) nested within studies. I would like to 
1) run a multilevel analysis with RVE correction to deal with this issue and then 
2) subdivide these studies across different subdomains to run subgroup analyses (e.g. 10 studies in subgroup A, 8 in subgroup B etc.). Would it therefore be appropriate to run the following 
 
# for the main multilevel analysis
General_model <-rma.mv(yi, vi, random = ~ 1 | Studies/Tasks, tdist=TRUE, data=df) 
 
# for the analysis with subgroups (The subdomain variable)
subgroup_analyses <-rma.mv(yi, vi, random = ~ 1 | Study/Tasks, tdist = TRUE, studlab= paste("Author","Task"),data = df,
                                 method = "REML",
                                 mods = ~ Subdomain)
 
# RVE 
subgroup_analyses _robust <-robust(subgroup_analyses, cluster = df$Study, adjust = TRUE)
 
Finally, could I create a forest plot for this robust multilevel analysis with the subgroups using the forest.rma function? As at present I am unable to plot it.
 
Thanks again for the help
 
Best,
Hellen
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