meta.MH {rmeta}R Documentation

Fixed effects (Mantel-Haenszel) meta-analysis

Description

Computes the individual odds ratios, the Mantel-Haenszel summary odds ratio, 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, names=NULL, data=NULL,
subset=NULL,conf.level=0.95)
summary.meta.MH(object,conf.level=NULL)
plot.meta.MH(object,summary=T,summlabel="Summary",...,conf.level=NULL,colors=list(box="black",lines="gray",summary="black",zero="lightgray"))

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
object a meta.MH object
summary Plot the summary odds ratio?
summlabel Label for the summary odds ratio
... other graphical arguments
conf.level Coverage for confidence intervals
colors colors for plotting. If this is a single color it will be used for all components, if NULL then par("fg") will be used

Value

An object of class meta.MH with print, plot and summary methods and components:

logOR log odds ratios for individual studies
selogOR standard errors for log odds ratios
logMH log of Mantel-Haenszel summary odds ratio
selogMH standard of summary log odds ratio
MHtest Mantel-Haenszel chisquare and p-value testing the hypothesis that the summary odds ratio is 1
het Woolf's chisquare for heterogeneity, its degrees of freedom and p-value
call A copy of the function call
names A copy of the vector of names

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

References

See Also

plot,par,meta.DSL

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(d,colors=NULL)