Function to add one or more polygons to a forest plot based on an object of class "predict.rma".

# S3 method for class 'predict.rma'
addpoly(x, rows=-2, annotate,
        addpred=FALSE, predstyle, predlim, digits, width, mlab,
        transf, atransf, targs, efac, col, border, lty, fonts, cex,
        constarea=FALSE, ...)

Arguments

x

an object of class "predict.rma".

rows

vector to specify the rows (or more generally, the positions) for plotting the polygons (defaults is -2). Can also be a single value to specify the row of the first polygon (the remaining polygons are then plotted below this starting row).

annotate

optional logical to specify whether annotations should be added to the plot for the polygons that are drawn.

addpred

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

predstyle

character string to specify the style of the prediction interval (either "line", "bar", "shade", or "dist"). Can be abbreviated. Setting this argument automatically sets addpred=TRUE.

predlim

optional argument to specify the limits of the prediction distribution when predstyle="dist".

digits

optional integer to specify the number of decimal places to which the annotations should be rounded.

width

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

mlab

optional character vector of the same length as x giving labels for the polygons that are drawn.

transf

optional argument to specify a function to transform the x values and confidence interval bounds (e.g., transf=exp; see also transf).

atransf

optional argument to specify a function to transform the annotations (e.g., atransf=exp; see also transf).

targs

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

efac

optional vertical expansion factor for the polygons.

col

optional character string to specify the color of the polygons.

border

optional character string to specify the border color of the polygons.

lty

optional argument to specify the line type for the prediction interval.

fonts

optional character string to specify the font for the labels and annotations.

cex

optional symbol expansion factor.

constarea

logical to specify whether the height of the polygons (when adding multiple) should be adjusted so that the area of the polygons is constant (the default is FALSE).

...

other arguments.

Details

The function can be used to add one or more polygons to an existing forest plot created with the forest function. For example, pooled estimates based on a model involving moderators can be added to the plot this way (see ‘Examples’).

To use the function, one should specify the values at which the polygons should be drawn (via the x argument) together with the corresponding variances (via the vi argument) or with the corresponding standard errors (via the sei argument). Alternatively, one can specify the values at which the polygons should be drawn together with the corresponding confidence interval bounds (via the ci.lb and ci.ub arguments). Optionally, one can also specify the bounds of the corresponding prediction interval bounds via the pi.lb and pi.ub arguments.

If unspecified, arguments annotate, digits, width, transf, atransf, targs, efac (only if the forest plot was created with forest.rma), fonts, cex, annosym, and textpos are automatically set equal to the same values that were used when creating the forest plot.

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 for functions to draw forest plots to which polygons can be added.

Examples

### calculate log risk ratios and corresponding sampling variances
dat <- escalc(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(dat, forest(yi, vi, atransf=exp, xlim=c(-9,5), ylim=c(-5,16),
                 at=log(c(0.05, 0.25, 1, 4)), cex=0.9, order=alloc,
                 ilab=alloc, ilab.lab="Allocation", ilab.xpos=-4.5,
                 header="Author(s) and Year"))

### fit mixed-effects model with allocation method as a moderator
res <- rma(yi, vi, mods = ~ 0 + alloc, data=dat)

### predicted log risk ratios for the different allocation methods
x <- predict(res, newmods=diag(3))

### add predicted average risk ratios to the forest plot
addpoly(x, efac=1.2, col="gray", addpred=TRUE,
        mlab=c("Alternate Allocation", "Random Allocation", "Systematic Allocation"))
abline(h=0)
text(-9, -1, "Model-Based Estimates:", pos=4, cex=0.9, font=2)