[R-meta] Questions about model averaging with complex multilevel meta-analytic model
m@@|e|n @end|ng |rom zoo|ogy@ubc@c@
Sat Sep 24 18:58:03 CEST 2022
I am PhD student at UBC in Vancouver, Canada, currently working on a meta-analysis. I have been trying to do model selection and model averaging using the model.sel() and model.avg() functions from the MuMIn package with an rma.mv model object, while also following your metafor help page using MuMIn and glmulti. I have been unable to get any of my models to perform model selection or model averaging because each model is being fit to different data. I have ensured there are no missing values or NAs across the data frame.
Is it possible to do model averaging with the rma.mv function with 3 level random effects, a phylogenetic correlation, and several moderators? There are currently no examples I could find using model selection or averaging with this model structure and I have had no luck on stack overflow.
Here is the full model I am trying to run:
mods = ~ I(flux_range-mean(flux_range))*I(mean_temp_constant-mean(mean_temp_constant))
+I(secondary_temp - mean(secondary_temp))*experiment_type
random = list( ~1 | phylo, ~1 | study_id, ~1 | response_id),
R = list(phylo=cor), test="t",
I have also tried using dredge() in MuMIn in addition to trying my own subset of models with no luck but it takes days for dredge() to iterate and still yields an error when trying to perform model averaging that none of the models are being fit to the same data. Any suggestions or assistance you can provide on this would be greatly appreciated.
<*)))><> <*)))><> <*)))><> <*)))><>
Maggie Slein (she/her/hers)
PhD Student, O’Connor Lab
Department of Zoology
Unceded xʷməθkʷəy̓əm (Musqueam) territory
University of British Columbia
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