Hello Wolfgang, I hope all is well. My name is Daniel, I am carrying out a multi-level meta-analysis using the metafor package, and I was hoping you could answer a quick question for me.
I am trying to assess publication bias using the PET method. To do this you include the inverse of the SE as a predictor in your model. In the code below, mods = ~ SE calls on the unweighted SE data from my dataframe. What I am unsure of is if the rma.mv function automatically weights "~SE" as 1/SE (as is needed for the PET method).
So do I need to calculate the weighted SE before including it in the model below, or does metafor do this for me?
overalleffectPET <- rma.mv(Tstat, Variance,
??????+ mods = ~ SE,
??????+ random = list(~ 1 | EffectSize_ID, ~ 1 | Study_ID),
??????+ tdist= TRUE, data=EmployBinaryITT)
Thank you in advance for both you time and help!
Daniel
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Daniel Foster, M.Ed.
PhD Candidate | Department of Applied Psychology and Human Development | University of Toronto
Research Associate | Atkinson Centre for Society and Child Development