Computes the individual odds ratio or relative risk, the
Mantel-Haenszel summary, 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.
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.MH(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.MH'
summary(object, conf.level=NULL, ...)
## S3 method for class 'meta.MH'
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
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.MH object
summary
Plot the summary odds ratio?
summlabel
Label for the summary odds ratio
conf.level
Coverage for confidence intervals
colors
see meta.colors
xlab
x-axis label, default is based on statistic
...
further arguments to be passed to or from methods.
Value
An object of class meta.MH with print, plot, funnelplot and
summary methods.
Note
There are at least two other ways to do a fixed effects
meta-analysis of binary data. Peto's method is a computationally
simpler approximation to the Mantel-Haenszel approach. It is also
possible to weight the individual odds ratios according to their
estimated variances. The Mantel-Haenszel method is superior if there
are trials with small numbers of events (less than 5 or so in either group)
Author(s)
Thomas Lumley
See Also
plot,par,meta.DSL,funnelplot
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))
a
summary(a)
plot(a)
d <- meta.MH(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))
d
summary(d)
## plot with par("fg")
plot(d, colors=meta.colors(NULL))