Add Polygons to Forest Plots (Method for 'rma' Objects)

Function to add a polygon to a forest plot showing the summary estimate with corresponding confidence interval based on an object of class "rma".

# S3 method for rma
addpoly(x, row=-2, level=x$level, annotate=TRUE,
        addpred=FALSE, digits=2, width, mlab, transf, atransf, targs,
        efac=1, col, border, lty, fonts, cex, ...)

Arguments

x

an object of class "rma".
row

numeric value to specify the row (or more generally, the horizontal position) for plotting the polygon (the default is -2).
level

numeric value between 0 and 100 to specify the confidence interval level (the default is to take the value from the object).
annotate

logical to specify whether annotations for the summary estimate should be added to the plot (the default is TRUE).
addpred

logical to specify whether the bounds of the prediction interval should be added to the plot (the default is FALSE).
digits

integer to specify the number of decimal places to which the annotations should be rounded (the default is 2).
width

optional integer to manually adjust the width of the columns for the annotations.
mlab

optional character string giving a label for the summary estimate polygon. If unspecified, the function sets a default label.
transf

optional argument to specify a function that should be used to transform the summary estimate and confidence interval bound (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
atransf

optional argument to specify a function that should be used to transform the annotations (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
targs

optional arguments needed by the function specified via transf or atransf.
efac

vertical expansion factor for the polygon. The default value of 1 should usually work okay.
col

optional character string to specify the name of a color to use for the polygon. If unspecified, the function sets a default color.
border

optional character string to specify the name of a color to use for the border of the polygon. If unspecified, the function sets a default color.
lty

optional character string to specify the line type for the prediction interval. If unspecified, the function sets this to "dotted" by default.
fonts

optional character string to specify the font to use for the label and annotations. If unspecified, the default font is used.
cex

optional symbol expansion factor. If unspecified, the function tries to set this to a sensible value.
...

other arguments.

Details

The function can be used to add a four-sided polygon, sometimes called a summary ‘diamond’, to an existing forest plot created with the forest function. The polygon shows the summary estimate (with its confidence interval bounds) based on a fixed- or random-effects model. Using this function, summary estimates based on different types of models can be shown in the same plot. Also, summary estimates based on a subgrouping of the studies can be added to the plot this way. See ‘Examples’.

The arguments transf, atransf, efac, and cex should always be set equal to the same values used to create the forest plot.

Author

Wolfgang Viechtbauer wvb@metafor-project.org https://www.metafor-project.org

References

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1--48. https://doi.org/10.18637/jss.v036.i03

See also

forest.rma, forest.default

Examples

### meta-analysis of the log risk ratios using the Mantel-Haenszel method
res <- rma.mh(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
              slab=paste(author, year, sep=", "))

### forest plot of the observed risk ratios with summary estimate
forest(res, atransf=exp, xlim=c(-8,6), ylim=c(-2.5,16), header=TRUE)


### meta-analysis of the log risk ratios using a random-effects model
res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### add summary estimate from the random-effects model to the forest plot
addpoly(res, atransf=exp)


### forest plot with subgrouping of studies and summaries per subgroup
res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
           slab=paste(author, year, sep=", "))
forest(res, xlim=c(-16, 4.6), at=log(c(.05, .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=.75, ylim=c(-1, 27),
       order=dat.bcg$alloc, rows=c(3:4,9:15,20:23),
       mlab="RE Model for All Studies", header="Author(s) and Year")

op <- par(cex=.75, 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"))

par(font=4)
text(-16, c(24,16,5), c("Systematic Allocation", "Random Allocation",
                        "Alternate Allocation"), pos=4)

par(op)
res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
           subset=(alloc=="systematic"))
addpoly(res, row=18.5, cex=.75, atransf=exp, mlab="RE Model for Subgroup")

res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
           subset=(alloc=="random"))
addpoly(res, row=7.5, cex=.75, atransf=exp, mlab="RE Model for Subgroup")

res <- rma(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
           subset=(alloc=="alternate"))
addpoly(res, row=1.5, cex=.75, atransf=exp, mlab="RE Model for Subgroup")