labbe.metabin  R Documentation 
Draw a L'Abbé plot for metaanalysis with binary outcomes.
## S3 method for class 'metabin' labbe( x, xlim, ylim, xlab = NULL, ylab = NULL, TE.common = x$TE.common, TE.random = x$TE.random, common = x$common, random = x$random, backtransf = x$backtransf, axes = TRUE, pch = 21, text = NULL, cex = 1, col = "black", bg = "lightgray", lwd = 1, lwd.common = lwd, lwd.random = lwd, lty.common = 2, lty.random = 9, col.common = col, col.random = col, nulleffect = TRUE, lwd.nulleffect = lwd, col.nulleffect = "lightgray", sm = x$sm, weight, studlab = FALSE, cex.studlab = 0.8, pos.studlab = 2, label.e = x$label.e, label.c = x$label.c, warn.deprecated = gs("warn.deprecated"), TE.fixed, fixed, lwd.fixed, lty.fixed, col.fixed, ... ) ## Default S3 method: labbe( x, y, xlim, ylim, xlab = NULL, ylab = NULL, TE.common = NULL, TE.random = NULL, common = !is.null(TE.common), random = !is.null(TE.random), backtransf = TRUE, axes = TRUE, pch = 21, text = NULL, cex = 1, col = "black", bg = "lightgray", lwd = 1, lwd.common = lwd, lwd.random = lwd, lty.common = 2, lty.random = 9, col.common = col, col.random = col, nulleffect = TRUE, lwd.nulleffect = lwd, col.nulleffect = "lightgray", sm = "", weight, studlab = FALSE, cex.studlab = 0.8, pos.studlab = 2, label.e = NULL, label.c = NULL, warn.deprecated = gs("warn.deprecated"), TE.fixed, fixed, lwd.fixed, lty.fixed, col.fixed, ... )
x 
An object of class 
xlim 
The x limits (min, max) of the plot. 
ylim 
The y limits (min, max) of the plot. 
xlab 
A label for the xaxis. 
ylab 
A label for the yaxis. 
TE.common 
A numeric or vector specifying combined common effect estimate(s). 
TE.random 
A numeric or vector specifying combined random effects estimate(s). 
common 
A logical indicating whether the common effect estimate should be plotted. 
random 
A logical indicating whether the random effects estimate should be plotted. 
backtransf 
A logical indicating which values should be printed on x and yaxis (see Details). 
axes 
A logical indicating whether axes should be drawn on the plot. 
pch 
The plotting symbol used for individual studies. 
text 
A character vector specifying the text to be used instead of plotting symbol. 
cex 
The magnification to be used for plotting symbol. 
col 
A vector with colour of plotting symbols. 
bg 
A vector with background colour of plotting symbols (only
used if 
lwd 
The line width. 
lwd.common 
The line width(s) for common effect estimate(s)
(if 
lwd.random 
The line width(s) for random effects estimate(s)
(if 
lty.common 
Line type(s) for common effect estimate(s). 
lty.random 
Line type(s) for random effects estimate(s). 
col.common 
Colour of line(s) for common effect estimate(s). 
col.random 
Colour of line(s) for random effects estimate(s). 
nulleffect 
A logical indicating whether line for null effect should be added to the plot.. 
lwd.nulleffect 
Width of line for null effect. 
col.nulleffect 
Colour of line for null effect. 
sm 
A character string indicating underlying summary measure,
i.e., 
weight 
Either a numeric vector specifying relative sizes of
plotting symbols or a character string indicating which type of
plotting symbols is to be used for individual treatment
estimates. One of missing (see Details), 
studlab 
A logical indicating whether study labels should be
printed in the graph. A vector with study labels can also be
provided (must be of same length as 
cex.studlab 
Size of study labels. 
pos.studlab 
Position of study labels, see argument

label.e 
Label for experimental group. 
label.c 
Label for control group. 
warn.deprecated 
A logical indicating whether warnings should be printed if deprecated arguments are used. 
TE.fixed 
Deprecated argument (replaced by 'TE.common'). 
fixed 
Deprecated argument (replaced by 'common'). 
lwd.fixed 
Deprecated argument (replaced by 'lwd.common'). 
lty.fixed 
Deprecated argument (replaced by 'lty.common'). 
col.fixed 
Deprecated argument (replaced by 'col.common'). 
... 
Graphical arguments as in 
y 
The y coordinates of the L'Abbé plot, if argument 
A L'Abbé plot is a scatter plot with the risk in the control group on the xaxis and the risk in the experimental group on the yaxis (L'Abbé et al., 1987). It can be used to evaluate heterogeneity in metaanalysis. Furthermore, this plot can aid to choose a summary measure (odds ratio, risk ratio, risk difference) that will result in more consistent results (Jiménez et al., 1997; Deeks, 2002).
If argument backtransf
is TRUE (default), event
probabilities will be printed on x and yaxis. Otherwise,
transformed event probabilities will be printed as defined by the
summary measure, i.e., log odds of probabilities for odds ratio as
summary measure (sm = "OR"
), log probabilities for sm
= "RR"
, and arcsinetransformed probabilities for sm =
"ASD"
.
If common
is TRUE, the estimate of the common effct model is
plotted as a line. If random
is TRUE, the estimate of the
random effects model is plotted as a line.
Information from object x
is utilised if argument
weight
is missing. Weights from the common effect model are
used (weight = "common"
) if argument x$common
is
TRUE
; weights from the random effects model are used
(weight = "random"
) if argument x$random
is
TRUE
and x$common
is FALSE
.
Guido Schwarzer sc@imbi.unifreiburg.de
Deeks JJ (2002): Issues in the selection of a summary statistic for metaanalysis of clinical trials with binary outcomes. Statistics in Medicine, 21, 1575–600
Jiménez FJ, Guallar E, MartínMoreno JM (1997): A graphical display useful for metaanalysis. European Journal of Public Health, 1, 101–5
L'Abbé KA, Detsky AS, O'Rourke K (1987): Metaanalysis in clinical research. Annals of Internal Medicine, 107, 224–33
metabin
data(Olkin1995) m1 < metabin(ev.exp, n.exp, ev.cont, n.cont, data = Olkin1995, studlab = paste(author, year), sm = "RR", method = "I") # L'Abbe plot for risk ratio # labbe(m1) # L'Abbe plot for odds ratio # labbe(m1, sm = "OR") # same plot labbe(update(m1, sm = "OR")) # L'Abbe plot for risk difference # labbe(m1, sm = "RD") # L'Abbe plot on log odds scale # labbe(m1, sm = "OR", backtransf = FALSE) # L'Abbe plot for odds ratio with coloured lines for various # treatment effects (defined as log odds ratios) # mycols < c("blue", "yellow", "green", "red", "green", "yellow", "blue") labbe(m1, sm = "OR", random = FALSE, TE.common = log(c(1 / 10, 1 / 5, 1 / 2, 1, 2, 5, 10)), col.common = mycols, lwd.common = 2) # L'Abbe plot on log odds scale with coloured lines for various # treatment effects (defined as log odds ratios) # labbe(m1, sm = "OR", random = FALSE, backtransf = FALSE, TE.common = log(c(1 / 10, 1 / 5, 1 / 2, 1, 2, 5, 10)), col.common = mycols, lwd.common = 2)
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