meta.MH {rmeta} | R Documentation |
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.
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"))
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 |
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 |
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)
Thomas Lumley
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)