Last data update: 2014.03.03
R: Meta-analysis plot (forest plot)
Meta-analysis plot (forest plot)
Description
Plot confidence intervals with boxes indicating the sample
size/precision and optionally a diamond indicating a summary
confidence interval. This function is usually called by plot
methods for meta-analysis objects.
Usage
metaplot(mn, se, nn=NULL, labels=NULL, conf.level=0.95,
xlab="Odds ratio", ylab="Study Reference",xlim=NULL,
summn=NULL, sumse=NULL, sumnn=NULL, summlabel="Summary",
logeffect=FALSE, lwd=2, boxsize=1,
zero=as.numeric(logeffect), colors=meta.colors(),
xaxt="s", logticks=TRUE, ...)
Arguments
mn
point estimates from studies
se
standard errors of mn
nn
precision: box ares is proportional to this. 1/se^2
is the default
labels
labels for each interval
conf.level
Confidence level for confidence intervals
xlab
label for the point estimate axis
ylab
label for the axis indexing the different studies
xlim
the range for the x axis.
summn
summary estimate
sumse
standard error of summary estimate
sumnn
precision of summary estimate
summlabel
label for summary estimate
logeffect
TRUE
to display on a log scale
lwd
line width
boxsize
Scale factor for box size
zero
"Null" effect value
xaxt
use "n"
for no x-axis (to add a customised one)
logticks
if TRUE
and logscale
, have tick values
approximately equally spaced on a log scale
.
colors
see meta.colors
...
Other graphical parameters
Value
This function is used for its side-effect.
See Also
forestplot
for more flexible plots
plot.meta.DSL
,
plot.meta.MH
,
plot.meta.summaries
Examples
data(catheter)
a <- meta.MH(n.trt, n.ctrl, col.trt, col.ctrl, data=catheter,
names=Name, subset=c(13,6,5,3,7,12,4,11,1,8,10,2))
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
logeffect=TRUE)
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
logeffect=TRUE,logticks=FALSE)
## angry fruit salad
metaplot(a$logOR, a$selogOR, nn=a$selogOR^-2, a$names,
summn=a$logMH, sumse=a$selogMH, sumnn=a$selogMH^-2,
logeffect=TRUE, colors=meta.colors(box="magenta",
lines="blue", zero="red", summary="orange",
text="forestgreen"))
Results