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

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", "polygon", "bar", "shade", or "dist"). Can be abbreviated. Setting this argument automatically sets addpred=TRUE.
predlim: optional argument to specify the limits of the predictive 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.

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

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)