[R-meta] Questions about interpreting the intercept in a rma.mv model
m@@|e|n @end|ng |rom zoo|ogy@ubc@c@
Mon May 22 21:19:12 CEST 2023
Thank you for the speedy reply, I really appreciate it. I have tried running your code from the second link you sent, but I have no luck in running the emmprep function --> am I missing something?
#install the dev version of metafor
#remotes::install_github("rvlenth/emmeans", dependencies = TRUE, build_opts = "")
trial <- rma.mv(yi, vi, mods = ~region + impact, method="ML", random = ~1|study_id, data=heatdome_ROM, dfs = "contain")
grd <- metafor::emmprep(trial) #this does not run
grd <- emmeans::emmprep(trial) #this does not run
grd <- emmprep(trial) #this does not run
Any assistance with this would be greatly appreciated.
On 5/19/23, 6:39 PM, "Reza Norouzian" <rnorouzian using gmail.com <mailto:rnorouzian using gmail.com>> wrote:
[CAUTION: Non-UBC Email]
This question has come up with some frequency on the list. For
example, in the archives
I found the following post:
which, I believe, exactly answers your questions.
On Fri, May 19, 2023 at 6:49 PM Slein, Margaret via
R-sig-meta-analysis <r-sig-meta-analysis using r-project.org <mailto:r-sig-meta-analysis using r-project.org>> wrote:
> Currently working on a meta-analysis and wondering about how to interpret the intercept in a rma.mv output with lnRR as the effect size and several binary categorical moderators? When I put in the -1 to remove the intercept, it doesn’t provide the full estimates for levels across all categorical moderators? How do I get the model output to provide estimates for all levels of all categorical moderators – is there an additional argument for this?
> Any help would be greatly appreciated.
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