Function to create forest plots for a given set of data.
# S3 method for default
forest(x, vi, sei, ci.lb, ci.ub, annotate=TRUE, showweights=FALSE,
xlim, alim, clim, ylim, at, steps=5,
level=95, refline=0, digits=2L, width,
xlab, slab, ilab, ilab.xpos, ilab.pos,
subset, transf, atransf, targs, rows,
efac=1, pch=15, psize, col, lty,
cex, cex.lab, cex.axis, annosym, …)vector of length \(k\) with the observed effect sizes or outcomes.
vector of length \(k\) with the corresponding sampling variances.
vector of length \(k\) with the corresponding standard errors.(note: only one of the two, vi or sei, needs to be specified)
vector of length \(k\) with the corresponding lower confidence intervals bounds. Not needed if vi or sei is specified. See ‘Details’.
vector of length \(k\) with the corresponding upper confidence intervals bounds. Not needed if vi or sei is specified. See ‘Details’.
logical specifying whether annotations should be added to the plot (the default is TRUE).
logical specifying whether the annotations should also include inverse variance weights (the default is FALSE).
horizontal limits of the plot region. If unspecified, the function tries to set the horizontal plot limits to some sensible values.
the actual x-axis limits. If unspecified, the function tries to set the x-axis limits to some sensible values.
limits for the confidence intervals. If unspecified, no limits are used.
the y limits of the plot. If unspecified, the function tries to set the y-axis limits to some sensible values.
position of the x-axis tick marks and corresponding labels. If unspecified, the function tries to set the tick mark positions/labels to some sensible values.
the number of tick marks for the x-axis (the default is 5). Ignored when the user specifies the positions via the at argument.
numerical value between 0 and 100 specifying the confidence interval level (the default is 95).
value at which a vertical ‘reference’ line should be drawn (the default is 0). The line can be suppressed by setting this argument to NA.
integer specifying the number of decimal places to which the tick mark labels of the x-axis and the annotations should be rounded (the default is 2L). Can also be a vector of two integers, the first specifying the number of decimal places for the annotations, the second for the x-axis labels. When specifying an integer (e.g., 2L), trailing zeros after the decimal mark are dropped for the x-axis labels. When specifying a numerical value (e.g., 2), trailing zeros are retained.
optional integer to manually adjust the width of the columns for the annotations.
title for the x-axis. If unspecified, the function tries to set an appropriate axis title.
optional vector with labels for the \(k\) studies. If unspecified, simple labels are created within the function. To suppress labels, set this argument to NA.
optional vector, matrix, or data frame providing additional information about the studies that should be added to the plot.
vector of numerical value(s) specifying the x-axis position(s) of the variable(s) given via ilab (must be specified if ilab is specified).
integer(s) (either 1, 2, 3, or 4) specifying the alignment of the vector(s) given via ilab (2 means right, 4 mean left aligned). If unspecified, the default is to center the labels.
optional vector indicating the subset of studies that should be used for the plot. This can be a logical vector of length \(k\) or a numeric vector indicating the indices of the observations to include. Note that this argument can also be used for reordering the studies.
optional argument specifying the name of a function that should be used to transform the observed effect sizes or outcomes and corresponding confidence interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
optional argument specifying the name of a function that should be used to transform the x-axis labels and annotations (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
optional arguments needed by the function specified via transf or atransf.
optional vector specifying the rows (or more generally, the horizontal positions) for plotting the outcomes. If unspecified, the function sets this value automatically. Can also be a single value specifying the row (horizontal position) of the first outcome (the remaining outcomes are then plotted below this starting row).
vertical expansion factor for confidence interval limits and arrows. The default value of 1 should usually work okay. Can also be a vector of two numbers, the first for CI limits, the second for arrows.
plotting symbol to use for the observed effect sizes or outcomes. By default, a filled square is used. See points for other options. Can also be a vector of values.
optional vector with point sizes for the observed effect sizes or outcomes. If unspecified, the point sizes are drawn proportional to the precision of the estimates.
optional character string specifying the name of a color to use for plotting ("black" is used by default if not specified). Can also be a vector of color names.
optional character string specifying the line type for the confidence intervals (if unspecified, the function sets this to "solid" by default).
optional character and symbol expansion factor. If unspecified, the function tries to set this to a sensible value.
optional expansion factor for the x-axis title. If unspecified, the function tries to set this to a sensible value.
optional expansion factor for the x-axis labels. If unspecified, the function tries to set this to a sensible value.
optional vector of length 3 to change the left bracket, separation, and right bracket symbols for the annotations.
other arguments.
The plot shows the individual observed effect sizes or outcomes with corresponding confidence intervals. To use the function, one should specify the observed effect sizes or outcomes (via the x argument) together with the corresponding sampling variances (via the vi argument) or with the corresponding standard errors (via the sei argument). Alternatively, one can specify the observed effect sizes or outcomes together with the corresponding confidence interval bounds (via the ci.lb and ci.ub arguments).
With the transf argument, the observed effect sizes or outcomes and corresponding confidence interval bounds can be transformed with some suitable function. For example, when plotting log odds ratios, then one could use transf=exp to obtain a forest plot showing the odds ratios. Alternatively, one can use the atransf argument to transform the x-axis labels and annotations (e.g., atransf=exp). See also transf for some transformation functions useful for meta-analyses. The examples below illustrate the use of these arguments.
By default, the studies are ordered from top to bottom (i.e., the first study in the dataset will be placed in row \(k\), the second study in row \(k-1\), and so on, until the last study, which is placed in the first row). The studies can be reordered with the subset argument (by specifying a vector with indices with the desired order).
Summary estimates can also be added to the plot with the addpoly function. See the documentation for that function for examples.
Lewis, S., & Clarke, M. (2001). Forest plots: Trying to see the wood and the trees. British Medical Journal, 322, 1479--1480.
Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1--48. http://www.jstatsoft.org/v36/i03/.
# NOT RUN {
### calculate log risk ratios and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
### default forest plot of the observed log risk ratios
forest(dat$yi, dat$vi)
### forest plot of the observed risk ratios
forest(dat$yi, dat$vi, slab=paste(dat$author, dat$year, sep=", "), transf=exp,
alim=c(0,2), steps=5, xlim=c(-2.5,4), refline=1, cex=.9)
### forest plot of the observed risk ratios
forest(dat$yi, dat$vi, slab=paste(dat$author, dat$year, sep=", "), atransf=exp,
at=log(c(.05,.25,1,4,20)), xlim=c(-10,8), cex=.9)
### forest plot of the observed risk ratios with studies ordered by the RRs
forest(dat$yi, dat$vi, slab=paste(dat$author, dat$year, sep=", "), atransf=exp,
at=log(c(.05,.25,1,4,20)), xlim=c(-10,8), cex=.9, subset=order(dat$yi))
### see also examples for the forest.rma function
# }
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