Draw a L'Abbé plot for metaanalysis with binary outcomes.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43  labbe(x, ...)
## Default S3 method:
labbe(x, y,
xlim, ylim,
xlab = NULL, ylab = NULL,
TE.fixed = NULL, TE.random = NULL,
comb.fixed = !is.null(TE.fixed), comb.random = !is.null(TE.random),
backtransf = TRUE,
axes = TRUE,
pch = 21, text = NULL, cex = 1,
col = "black", bg = "lightgray",
lwd = 1, lwd.fixed = lwd, lwd.random = lwd,
lty.fixed = 2, lty.random = 9,
col.fixed = col, col.random = col,
nulleffect = TRUE,
lwd.nulleffect = lwd, col.nulleffect = "lightgray",
sm = NULL, weight,
studlab = FALSE, cex.studlab = 0.8,
label.e = NULL, label.c = NULL,
...)
## S3 method for class 'metabin'
labbe(x,
xlim, ylim,
xlab = NULL, ylab = NULL,
TE.fixed = x$TE.fixed,
TE.random = x$TE.random,
comb.fixed = x$comb.fixed,
comb.random = x$comb.random,
backtransf = x$backtransf,
axes = TRUE,
pch = 21, text = NULL, cex = 1,
col = "black", bg = "lightgray",
lwd = 1, lwd.fixed = lwd, lwd.random = lwd,
lty.fixed = 2, lty.random = 9,
col.fixed = col, col.random = col,
nulleffect = TRUE,
lwd.nulleffect = lwd, col.nulleffect = "lightgray",
sm = x$sm, weight,
studlab = FALSE, cex.studlab = 0.8,
label.e = x$label.e, label.c = x$label.c,
...)

x 
The x coordinates of points of the L'Abbé
plot. Alternatively, an object of class 
y 
The y coordinates of the L'Abbé plot, optional if 
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.fixed 
A numeric or vector specifying combined fixed effect estimate(s). 
TE.random 
A numeric or vector specifying combined random effects estimate(s). 
comb.fixed 
A logical indicating whether the pooled fixed effect estimate should be plotted. 
comb.random 
A logical indicating whether the pooled 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.fixed 
The line width(s) for fixed effect estimate(s) (if

lwd.random 
The line width(s) for random effects estimate(s)
(if 
lty.fixed 
Line type(s) for fixed effect estimate(s). 
lty.random 
Line type(s) for random effects estimate(s). 
col.fixed 
Color of line(s) for fixed effect estimate(s). 
col.random 
Color 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 
Color 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. 
label.e 
Label for experimental group. 
label.c 
Label for control group. 
... 
Graphical arguments as in 
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.
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 comb.fixed
is TRUE, the pooled estimate of the fixed effect
model is plotted as a line. If comb.random
is TRUE, the pooled
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 fixed effect model are
used (weight = "fixed"
) if argument x$comb.fixed
is
TRUE
; weights from the random effects model are used
(weight = "random"
) if argument x$comb.random
is
TRUE
and x$comb.fixed
is FALSE
.
Guido Schwarzer sc@imbi.unifreiburg.de
L'Abbé KA, Detsky AS, O'Rourke K (1987), Metaanalysis in clinical research. Annals of Internal Medicine, 107, 224–233.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46  data(Olkin95)
meta1 < metabin(event.e, n.e, event.c, n.c,
data = Olkin95,
studlab = paste(author, year),
sm = "RR", method = "I")
#
# L'Abbe plot for risk ratio
#
labbe(meta1)
# L'Abbe plot for odds ratio
#
labbe(meta1, sm = "OR")
# same plot
labbe(update(meta1, sm = "OR"))
# L'Abbe plot for risk difference
#
labbe(meta1, sm = "RD")
# L'Abbe plot on log odds scale
#
labbe(meta1, 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(meta1, sm = "OR",
comb.random = FALSE,
TE.fixed = log(c(1 / 10, 1 / 5, 1 / 2,
1, 2, 5, 10)),
col.fixed = mycols, lwd.fixed = 2)
# L'Abbe plot on log odds scale with coloured lines for various
# treatment effects (defined as log odds ratios)
#
labbe(meta1, sm = "OR",
comb.random = FALSE,
TE.fixed = log(c(1 / 10, 1 / 5, 1 / 2,
1, 2, 5, 10)),
col.fixed = mycols, lwd.fixed = 2,
backtransf = FALSE)

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