bubble.metareg | R Documentation |
Draw a bubble plot to display the result of a meta-regression.
## S3 method for class 'metareg'
bubble(
x,
xlim,
ylim,
xlab,
ylab,
cex,
min.cex = 0.5,
max.cex = 5,
pch = 21,
col = "black",
bg = "darkgray",
lty = 1,
lwd = 1,
col.line = "black",
studlab = FALSE,
cex.studlab = 0.8,
pos.studlab = 2,
offset = 0.5,
regline = TRUE,
backtransf = x$.meta$x$backtransf,
ref,
col.ref = "lightgray",
lty.ref = 1,
lwd.ref = 1,
pscale = x$.meta$x$pscale,
irscale = x$.meta$x$irscale,
axes = TRUE,
box = TRUE,
...
)
bubble(x, ...)
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 x-axis. |
ylab |
A label for the y-axis. |
cex |
The magnification to be used for plotting symbols. |
min.cex |
Minimal magnification for plotting symbols. |
max.cex |
Maximal magnification for plotting symbols. |
pch |
The plotting symbol(s) used for individual studies. |
col |
A vector with colour of plotting symbols. |
bg |
A vector with background colour of plotting symbols (only
used if |
lty |
The line type for the meta-regression line. |
lwd |
The line width for the meta-regression line. |
col.line |
Colour for the meta-regression line. |
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 the numer of studies in the meta-analysis then). |
cex.studlab |
The magnification for study labels. |
pos.studlab |
Position of study labels, see argument
|
offset |
Offset for study labels (see |
regline |
A logical indicating whether a regression line should be added to the bubble plot. |
backtransf |
A logical indicating whether results for relative
summary measures (argument |
ref |
A numerical giving the reference value to be plotted as
a line in the bubble plot. No reference line is plotted if
argument |
col.ref |
Colour of the reference line. |
lty.ref |
The line type for the reference line. |
lwd.ref |
The line width for the reference line. |
pscale |
A numeric giving scaling factor for printing of probabilities. |
irscale |
A numeric defining a scaling factor for printing of incidence rates. |
axes |
Either a logical or a character string equal to |
box |
A logical indicating whether a box should be printed. |
... |
Graphical arguments as in |
A bubble plot can be used to display the result of a meta-regression. It is a scatter plot with the treatment effect for each study on the y-axis and the covariate used in the meta-regression on the x-axis. Typically, the size of the plotting symbol is inversely proportional to the variance of the estimated treatment effect (Thompson & Higgins, 2002).
Argument cex
specifies the plotting size for each individual
study. If this argument is missing the weights from the
meta-regression model will be used (which typically is a random
effects model). Use cex="common"
in order to utilise weights
from a common effect model to define the size of the plotted
symbols (even for a random effects meta-regression). If a vector
with individual study weights is provided, the length of this
vector must be of the same length as the number of studies.
Arguments min.cex
and max.cex
can be used to define
the size of the smallest and largest plotting symbol. The plotting
size of the most precise study is set to max.cex
whereas the
plotting size of all studies with a plotting size smaller than
min.cex
will be set to min.cex
.
For a meta-regression with more than one covariate. Only a scatter plot of the first covariate in the regression model is shown. In this case the effect of the first covariate adjusted for other covariates in the meta-regression model is shown.
For a factor or categorial covariate separate bubble plots for each group compared to the baseline group are plotted.
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
Thompson SG, Higgins JP (2002): How should meta-regression analyses be undertaken and interpreted? Statistics in Medicine, 21, 1559–73
metagen
, metainf
data(Fleiss1993cont)
# Add some (fictitious) grouping variables:
Fleiss1993cont$age <- c(55, 65, 52, 65, 58)
Fleiss1993cont$region <- c("Europe", "Europe", "Asia", "Asia", "Europe")
m1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
data = Fleiss1993cont, sm = "SMD")
mr1 <- metareg(m1, region)
mr1
bubble(mr1)
bubble(mr1, lwd = 2, col.line = "blue")
mr2 <- metareg(m1, age)
mr2
bubble(mr2, lwd = 2, col.line = "blue", xlim = c(50, 70))
bubble(mr2, lwd = 2, col.line = "blue", xlim = c(50, 70), cex = "common")
# Do not print regression line
#
bubble(mr2, lwd = 2, col.line = "blue", xlim = c(50, 70), regline = FALSE)
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