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)
summary.meta.MH(object)
plot.meta.MH(object,summary=T,summlabel="Summary",...)

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

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)


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