The metafor Package

A Meta-Analysis Package for R

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plots:forest_plot_with_subgroups

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Forest Plot with Subgroups

Description

Below is an example of a forest plot with three subgroups. The results of the individual studies are shown grouped together according to their subgroup. Below each subgroup, a summary polygon shows the results when fitting a random-effects model just to the studies within that group. The summary polygon at the bottom of the plot shows the results from a random-effects model when analyzing all 13 studies.

Code

library(metafor)

### decrease margins so the full space is used
par(mar=c(4,4,1,2))

### fit random-effects model (use slab argument to define study labels)
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
slab=paste(author, year, sep=", "), method="REML")

### set up forest plot (with 2x2 table counts added; rows argument is used
### to specify exactly in which rows the outcomes will be plotted)
forest(res, xlim=c(-16, 6), at=log(c(0.05, 0.25, 1, 4)), atransf=exp,
ilab=cbind(dat.bcg$tpos, dat.bcg$tneg, dat.bcg$cpos, dat.bcg$cneg),
ilab.xpos=c(-9.5,-8,-6,-4.5), cex=0.75, ylim=c(-1, 27),
order=order(dat.bcg$alloc), rows=c(3:4,9:15,20:23), xlab="Risk Ratio", mlab="", psize=1) ### add text with Q-value, dfs, p-value, and I^2 statistic text(-16, -1, pos=4, cex=0.75, bquote(paste("RE Model for All Studies (Q = ", .(formatC(res$QE, digits=2, format="f")), ", df = ", .(res$k - res$p),
", p = ", .(formatC(res$QEp, digits=2, format="f")), "; ", I^2, " = ", .(formatC(res$I2, digits=1, format="f")), "%)")))

### set font expansion factor (as in forest() above) and use bold italic
### font and save original settings in object 'op'
op <- par(cex=0.75, font=4)

### add text for the subgroups
text(-16, c(24,16,5), pos=4, c("Systematic Allocation",
"Random Allocation",
"Alternate Allocation"))

### switch to bold font
par(font=2)

text(c(-9.5,-8,-6,-4.5), 26, c("TB+", "TB-", "TB+", "TB-"))
text(c(-8.75,-5.25),     27, c("Vaccinated", "Control"))
text(-16,                26, "Author(s) and Year",  pos=4)
text(6,                  26, "Risk Ratio [95% CI]", pos=2)

### set par back to the original settings
par(op)

### fit random-effects model in the three subgroups
res.s <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
subset=(alloc=="systematic"), method="REML")
res.r <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
subset=(alloc=="random"), method="REML")
res.a <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
subset=(alloc=="alternate"), method="REML")

### add summary polygons for the three subgroups
addpoly(res.r, row= 7.5, cex=0.75, atransf=exp, mlab="")
addpoly(res.a, row= 1.5, cex=0.75, atransf=exp, mlab="")

### add text with Q-value, dfs, p-value, and I^2 statistic for subgroups
text(-16, 18.5, pos=4, cex=0.75, bquote(paste("RE Model for Subgroup (Q = ",
.(formatC(res.s$QE, digits=2, format="f")), ", df = ", .(res.s$k - res.s$p), ", p = ", .(formatC(res.s$QEp, digits=2, format="f")), "; ", I^2, " = ",
.(formatC(res.s$I2, digits=1, format="f")), "%)"))) text(-16, 7.5, pos=4, cex=0.75, bquote(paste("RE Model for Subgroup (Q = ", .(formatC(res.r$QE, digits=2, format="f")), ", df = ", .(res.r$k - res.r$p),
", p = ", .(formatC(res.r$QEp, digits=2, format="f")), "; ", I^2, " = ", .(formatC(res.r$I2, digits=1, format="f")), "%)")))
text(-16, 1.5, pos=4, cex=0.75, bquote(paste("RE Model for Subgroup (Q = ",
.(formatC(res.a$QE, digits=2, format="f")), ", df = ", .(res.a$k - res.a$p), ", p = ", .(formatC(res.a$QEp, digits=2, format="f")), "; ", I^2, " = ",
.(formatC(res.a\$I2, digits=1, format="f")), "%)")))