baujat.meta | R Documentation |
Draw a Baujat plot to explore heterogeneity in meta-analysis.
## S3 method for class 'meta'
baujat(
x,
yscale = 1,
xlim,
ylim,
xlab = "Contribution to overall heterogeneity",
ylab = "Influence on overall result",
pch = 21,
cex = 1,
col = "black",
bg = "darkgray",
studlab = TRUE,
cex.studlab = 0.8,
pos.studlab,
offset = 0.5,
xmin = 0,
ymin = 0,
grid = TRUE,
col.grid = "lightgray",
lty.grid = "dotted",
lwd.grid = par("lwd"),
pty = "s",
pooled,
...
)
x |
An object of class |
yscale |
Scaling factor for values on y-axis. |
xlim |
The x limits (min,max) of the plot. |
ylim |
The y limits (min,max) of the plot. |
xlab |
A label for the x-axis. |
ylab |
A label for the y-axis. |
pch |
The plotting symbol used for individual studies. |
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 |
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 |
The magnification for study labels. |
pos.studlab |
Position of study labels, see argument
|
offset |
Offset for study labels (see |
xmin |
A numeric specifying minimal value to print study labels (on x-axis). |
ymin |
A numeric specifying minimal value to print study labels (on y-axis). |
grid |
A logical indicating whether a grid is printed in the plot. |
col.grid |
Colour for grid lines. |
lty.grid |
The line type for grid lines. |
lwd.grid |
The line width for grid lines. |
pty |
A character specifying type of plot region (see
|
pooled |
A character string indicating whether a common effect
or random effects model is used for pooling. Either missing (see
Details), |
... |
Graphical arguments as in |
Baujat et al. (2002) introduced a scatter plot to explore
heterogeneity in meta-analysis. On the x-axis the contribution of
each study to the overall heterogeneity statistic (see list object
Q
of the meta-analysis object x
) is plotted. On the
y-axis the standardised difference of the overall treatment effect
with and without each study is plotted; this quantity describes the
influence of each study on the overal treatment effect.
Information from object x
is utilised if argument
pooled
is missing. A common effect model is assumed
(pooled="common"
) if argument x$common
is
TRUE
; a random effects model is assumed
(pooled="random"
) if argument x$random
is
TRUE
and x$common
is FALSE
.
Internally, the metainf
function is used to calculate
the values on the y-axis.
A data.frame with the following variables:
x |
Coordinate on x-axis (contribution to heterogeneity statistic) |
y |
Coordinate on y-axis (influence on overall treatment effect) |
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
Baujat B, Mahé C, Pignon JP, Hill C (2002): A graphical method for exploring heterogeneity in meta-analyses: Application to a meta-analysis of 65 trials. Statistics in Medicine, 30, 2641–52
metagen
, metainf
data(Olkin1995)
# Only consider first ten studies
m1 <- metabin(ev.exp, n.exp, ev.cont, n.cont,
data = Olkin1995, sm = "OR", method = "I", studlab = paste(author, year),
subset = 1:10)
# Generate Baujat plot
baujat(m1)
## Not run:
m1 <- metabin(ev.exp, n.exp, ev.cont, n.cont,
data = Olkin1995, sm = "OR", method = "I", studlab = paste(author, year))
# Do not print study labels if the x-value is smaller than 4 and
# the y-value is smaller than 1
baujat(m1, yscale = 10, xmin = 4, ymin = 1)
# Change position of study labels
baujat(m1, yscale = 10, xmin = 4, ymin = 1,
pos = 1, xlim = c(0, 6.5))
# Generate Baujat plot and assign x- and y- coordinates to R object
# b1
b1 <- baujat(m1)
# Calculate overall heterogeneity statistic
sum(b1$x)
m1$Q
## End(Not run)
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