meta.MH {rmeta} | R Documentation |
Fixed effects (Mantel-Haenszel) meta-analysis
Description
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 |
statistic |
"OR" for odds ratio, "RR" for relative risk |
x , object |
a |
summary |
Plot the summary odds ratio? |
summlabel |
Label for the summary odds ratio |
conf.level |
Coverage for confidence intervals |
colors |
see |
xlab |
x-axis label, default is based on |
... |
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
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))