Hi Dylan,
Here is an example using rma(), but the same principle applies to models fitted with rma.mv().
dat <- dat.bcg
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat)
res <- rma(yi, vi, data=dat)
res.r <- rma(yi, vi, data=dat, subset=alloc=="random")
res.n <- rma(yi, vi, data=dat, subset=alloc!="random")
dev.new(width=10, height=6)
forest(c(coef(res.r), coef(res.n), coef(res)),
c(vcov(res.r), vcov(res.n), vcov(res)),
slab=c("With Random Assignment", "Without Random Assignment", "All Studies"),
header=c("Subset", "Risk Ratio [95% CI]"), xlab="Risk Ratio (log scale)",
top=2, refline=NA, xlim=c(-3,1), atransf=exp, at=log(c(.2, .5, 1)), psize=1, efac=0)
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org]
On Behalf Of Dylan Johnson
Sent: Sunday, 20 December, 2020 2:01
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] Putting pooled effects from different multilevel meta
analyses into the same forest plot
Hello,
I am currently using the rma.mv function to carry out my metas and would
like to display two pooled subgroups from one of them and an additional
pooled estimate from another.
Is there anyways to go about doing this?
Many thanks!
Dylan
Dylan Johnson, MSc
MA Student, School and Clinical Child Psychology
Department of Applied Psychology and Human Development
University of Toronto
252 Bloor Street West
Toronto, ON M5S 1V6