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metafor (version 1.9-2)

forest.cumul.rma: Forest Plots for 'cumul.rma' Objects

Description

Function to create forest plots for objects of class "cumul.rma".

Usage

## S3 method for class 'cumul.rma':
forest(x, annotate=TRUE, xlim, alim, ylim, at, steps=5,
       level=x$level, digits=2, refline=0, xlab,
       ilab, ilab.xpos, ilab.pos,
       transf=FALSE, atransf=FALSE, targs, rows,
       efac=1, pch=15, psize=1,
       cex, cex.lab, cex.axis, \dots)

Arguments

x
an object of class "cumul.rma".
annotate
logical specifying whether annotations should be added to the plot (default is TRUE).
xlim
horizontal limits of the plot region. If unspecified, the function tries to set the horizontal plot limits to some sensible values.
alim
the actual x-axis limits. If unspecified, the function tries to set the x-axis limits to some sensible values.
ylim
the y limits of the plot. If unspecified, the function tries to set the y-axis limits to some sensible values.
at
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.
steps
the number of tick marks for the x-axis (default is 5). Ignored when the user specifies the positions via the at argument.
level
numerical value between 0 and 100 specifying the confidence interval level (the default is to take the value from the object).
digits
integer specifying the number of decimal places to which the tick mark labels of the x-axis and the annotations should be rounded (default is 2). Can also be a vector of two integers, the first specifying the number of decimal places for the annotations,
refline
value at which a vertical reference line should be drawn (default is 0). The line can be suppressed by setting this argument to NA.
xlab
title for the x-axis. If unspecified, the function tries to set an appropriate axis title.
ilab
optional vector or matrix of character strings providing additional information about the studies.
ilab.xpos
vector of numerical value(s) specifying the x-axis position(s) of the character vector(s) given via ilab (must be specified if ilab is specified).
ilab.pos
integer(s) (either 1, 2, 3, or 4) specifying the alignment of the character vector(s) given via ilab (2 means right, 4 means left aligned). If unspecified, the default is to center the labels.
transf
optional argument specifying the name of a function that should be used to transform the observed effect sizes, summary estimates, fitted values, and confidence interval bounds (e.g., transf=exp). Defaults to FALSE, which means t
atransf
optional argument specifying the name of a function that should be used to transform the x-axis labels and annotations (e.g., transf=exp). Defaults to FALSE, which means that no transformation is used.
targs
optional arguments needed by the function specified via transf or atransf.
rows
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 outco
efac
vertical expansion factor for arrows, confidence interval limits, and the symbol used to denote summary estimates. The default value of 1 should usually work okay.
pch
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.
psize
optional vector with point sizes for the observed effect sizes or outcomes. Default is 1.
cex
optional character and symbol expansion factor. If unspecified, the function tries to set this to a sensible value.
cex.lab
optional expansion factor for the x-axis titel. If unspecified, the function tries to set this to a sensible value.
cex.axis
optional expansion factor for the x-axis labels. If unspecified, the function tries to set this to a sensible value.
...
other arguments.

Details

The plot shows the estimated (average) outcome with corresponding confidence interval as one study at a time is added to the analysis.

References

Chalmers, T. C., & Lau, J. (1993). Meta-analytic stimulus for changes in clinical trials. Statistical Methods in Medical Research, 2, 161--172. Lau, J., Schmid, C. H., & Chalmers, T. C. (1995). Cumulative meta-analysis of clinical trials builds evidence for exemplary medical care. Journal of Clinical Epidemiology, 48, 45--57. 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/.

See Also

forest, cumul

Examples

Run this code
### load BCG vaccine data
data(dat.bcg)

### calculate log relative risks and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### random-effects model
res <- rma(yi, vi, data=dat, method="REML", slab=paste(author, year, sep=", "))

x <- cumul(res, order=order(dat$year))
forest(x)
forest(x, alim=c(-2,1))

### meta-analysis of the (log) relative risks using the Mantel-Haenszel method
res <- rma.mh(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg,
              measure="RR", slab=paste(author, year, sep=", "))
x <- cumul(res, order=order(dat$year))
forest(x, alim=c(-2,1))

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