R: Random effects (DerSimonian-Laird) meta-analysis
meta.DSL
R Documentation
Random effects (DerSimonian-Laird) meta-analysis
Description
Computes the individual odds ratios or relative risks, the summary, the random
effects variance, and Woolf's test for heterogeneity. The print
method gives the summary and test for heterogeneity; the summary
method also gives all the individual odds ratios and confidence
intervals. Studies with zero or infinite odds ratio are omitted, as
their variance cannot be calculated sensibly.
The plot method draws a standard meta-analysis plot. The
confidence interval for each study is given by a horizontal line, and
the point estimate is given by a square whose height is inversely
proportional to the standard error of the estimate. The summary odds
ratio, if requested, is drawn as a diamond with horizontal limits at the
confidence limits and width inversely proportional to its standard
error.
Usage
meta.DSL(ntrt, nctrl, ptrt, pctrl, conf.level=0.95,
names=NULL, data=NULL, subset=NULL, na.action=na.fail,statistic="OR")
## S3 method for class 'meta.DSL'
summary(object, conf.level=NULL, ...)
## S3 method for class 'meta.DSL'
plot(x, summary=TRUE, summlabel="Summary",
conf.level=NULL, colors=meta.colors(), xlab=NULL,...)
Arguments
ntrt
Number of subjects in treated/exposed group
nctrl
Number of subjects in control group
ptrt
Number of events in treated/exposed group
pctrl
Number of events in control group
conf.level
Coverage for confidence intervals
names
names or labels for studies
data
data frame to interpret variables
subset
subset of studies to include
na.action
a function which indicates what should happen when
the data contain NAs. Defaults to na.fail.
statistic
"OR" for odds ratio, "RR" for relative risk
x,object
a meta.DSL object
summary
Plot the summary odds ratio?
summlabel
Label for the summary odds ratio
colors
see meta.colors
xlab
x-axis label, default is based on statistic
...
further arguments to be passed from or to methods.
Value
An object of class meta.DSL with print, plot, funnelplot and
summary methods.
Author(s)
Thomas Lumley
See Also
plot,par,meta.MH,funnelplot
Examples
data(catheter)
b <- meta.DSL(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))
b
summary(b)
plot(b)
e <- meta.DSL(n.trt, n.ctrl, inf.trt, inf.ctrl, data=catheter,
names=Name, subset=c(13,6,3,12,4,11,1,14,8,10,2))
e
summary(e)
##tasteless
plot(e, colors=meta.colors(summary="green",lines="purple",box="orange"))