[R-meta] Plotting interaction effect from a rma.mv() fit

Simon Harmel @|m@h@rme| @end|ng |rom gm@||@com
Tue Mar 16 17:49:08 CET 2021


Dear Michael,

Thank you. I would certainly be interested in seeing what exactly you mean
by using `forest.default()` to display an interaction effect for my model
(below)?

library(metafor)
dat <- read.csv("https://raw.githubusercontent.com/hkil/m/master/tst.csv")
fit <- rma.mv(d ~ factor(outcome)*time, V = SE^2, random= ~1|id, data = dat)


On Tue, Mar 16, 2021 at 11:39 AM Michael Dewey <lists using dewey.myzen.co.uk>
wrote:

> Dear Simon
>
> If you do not want to load extra packages effect plots (or something
> similar) can be obtained with forest.default() once your have the
> required data from predict().
>
> Michael
>
> On 16/03/2021 14:25, Simon Harmel wrote:
> > Highly appreciated, Wolfgang!
> >
> >
> >
> > On Tue, Mar 16, 2021 at 5:12 AM Viechtbauer, Wolfgang (SP) <
> > wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> >
> >> Dear Simon,
> >>
> >> Not aware of any packages that interface with rma.mv, but this is
> >> relatively easy to do by hand. Just use predict() with the newmods
> argument
> >> to compute the predicted values as a function of 'time' for each level
> of
> >> 'outcome' and then create a plot with those lines.
> >>
> >> Best,
> >> Wolfgang
> >>
> >>> -----Original Message-----
> >>> From: R-sig-meta-analysis [mailto:
> >> r-sig-meta-analysis-bounces using r-project.org] On
> >>> Behalf Of Simon Harmel
> >>> Sent: Tuesday, 16 March, 2021 5:25
> >>> To: R meta
> >>> Subject: [R-meta] Plotting interaction effect from a rma.mv() fit
> >>>
> >>> Dear All,
> >>>
> >>> Are there plotting packages (e.g., `effects::plot(allEffects())`,
> >>> `sjPlot::plot_model()`, `emmeans::emmip()`  ) to plot the predictions
> of a
> >>> say rma.mv() model?
> >>>
> >>> For example, is it possible to plot the interaction effect below?
> >>>
> >>> library(metafor)
> >>> dat <- read.csv("
> https://raw.githubusercontent.com/hkil/m/master/tst.csv
> >> ")
> >>> fit <- rma.mv(d ~ factor(outcome)*time, V = SE^2, random= ~1|id, data
> =
> >> dat)
> >>
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
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> > R-sig-meta-analysis using r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
> >
>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
>

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