I am conducting a meta-analysis using the robust variance estimation (RVE) technique due to the fact that each study contains multiple effect sizes. In my case, effect sizes are r (linear association). After extensive online research, I decided to use robumeta package in R, and robu function to calculate the overall effect size across all studies. Below is my main model and data structure in R.
`run.average <- robu(formula = Correlation ~ 1,
var.eff.size = Varience,
data = d2,
studynum = ID,
modelweights = "CORR")`
My goal is to create a forest plot to display the weighted mean effect size for each study (so, each study only has 1 effect size).
As far as I know, forest.robu() can plot each effect size, which, however, is not what I need. Using other functions like forest() may not apply to RVE model.
Therefore, I wonder if there is any solution to creating a forest plot for weighted mean effect size for each study.
