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--- plots:forest_plot_with_subgroups [2020/03/19 13:31] – Wolfgang Viechtbauer
+++ plots:forest_plot_with_subgroups [2020/06/03 07:36] – Wolfgang Viechtbauer
@@ Line 14: / Line 14: @@
 library(metafor)
-### decrease margins so the full space is used
+### copy BCG vaccine meta-analysis data into 'dat'
-par(mar=c(4,4,1,2))
+dat <- dat.bcg
-### fit random-effects model (use slab argument to define study labels)
+### calculate log risk ratios and corresponding sampling variances (and use
-res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
+### the 'slab' argument to store study labels as part of the data frame)
-           slab=paste(author, year, sep=", "), method="REML")
+dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat,
+              slab=paste(author, year, sep=", "))
-### set up forest plot (with 2x2 table counts added; rows argument is used
+### fit random-effects model
-### to specify exactly in which rows the outcomes will be plotted)
+res <- rma(yi, vi, data=dat)
+### set up forest plot (with 2x2 table counts added; the 'rows' argument is
+### used to specify 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=cbind(dat$tpos, dat$tneg, dat$cpos, dat$cneg),
        ilab.xpos=c(-9.5,-8,-6,-4.5), cex=0.75, ylim=c(-1, 27),
-       order=order(dat.bcg$alloc), rows=c(3:4,9:15,20:23),
+       order=order(dat$alloc), rows=c(3:4,9:15,20:23),
        xlab="Risk Ratio", mlab="", psize=1, header="Author(s) and Year")
@@ Line 34: / Line 38: @@
      ", p = ", .(formatC(res$QEp, digits=2, format="f")), "; ", I^2, " = ",
      .(formatC(res$I2, digits=1, format="f")), "%)")))
+### fit meta-regression model to test for subgroup differences
+res <- rma(yi, vi, mods = ~ alloc, data=dat)
+### add text for the test of subgroup differences
+text(-16, -1.8, pos=4, cex=0.75, bquote(paste("Test for Subgroup Differences: ",
+     Q[M], " = ", .(formatC(res$QM, digits=2, format="f")), ", df = ", .(res$p - 1),
+     ", p = ", .(formatC(res$QMp, digits=2, format="f")))))
 ### set font expansion factor (as in forest() above) and use bold italic
@@ Line 55: / Line 67: @@
 ### fit random-effects model in the three subgroups
-res.s <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
+res.s <- rma(yi, vi, subset=(alloc=="systematic"), data=dat)
-             subset=(alloc=="systematic"), method="REML")
+res.r <- rma(yi, vi, subset=(alloc=="random"), data=dat)
-res.r <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg, measure="RR",
+res.a <- rma(yi, vi, subset=(alloc=="alternate"), data=dat)
-             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