meta.MH: Fixed effects (Mantel-Haenszel) meta-analysis

In rmeta: 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 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))

Example output

Fixed effects ( Mantel-Haenszel ) Meta-Analysis
Call: meta.MH(ntrt = n.trt, nctrl = n.ctrl, ptrt = col.trt, pctrl = col.ctrl, 
    names = Name, data = catheter, subset = c(13, 6, 5, 3, 7, 
        12, 4, 11, 1, 8, 10, 2))
Mantel-Haenszel OR =0.44    95% CI ( 0.36, 0.54 )
Test for heterogeneity: X^2( 10 ) = 25.36 ( p-value 0.0047 )
Fixed effects ( Mantel-Haenszel ) meta-analysis
Call: meta.MH(ntrt = n.trt, nctrl = n.ctrl, ptrt = col.trt, pctrl = col.ctrl, 
    names = Name, data = catheter, subset = c(13, 6, 5, 3, 7, 
        12, 4, 11, 1, 8, 10, 2))
------------------------------------
             OR (lower  95% upper)
Tennenberg 0.22    0.10       0.49
Maki       0.49    0.29       0.82
vanHeerden 0.27    0.07       1.00
Hannan     0.83    0.40       1.72
Bach(a)     NaN    0.00        NaN
Bach(b)    0.11    0.02       0.49
Heard      0.60    0.38       0.95
Collins    0.10    0.02       0.41
Ciresi     0.69    0.34       1.42
Ramsay     0.58    0.37       0.92
Trazzera   0.47    0.23       0.94
George     0.12    0.04       0.33
------------------------------------
Mantel-Haenszel OR =0.44 95% CI ( 0.36,0.54 )
Test for heterogeneity: X^2( 10 ) = 25.36 ( p-value 0.0047 )
Fixed effects ( Mantel-Haenszel ) Meta-Analysis
Call: meta.MH(ntrt = n.trt, nctrl = n.ctrl, ptrt = inf.trt, pctrl = inf.ctrl, 
    names = Name, data = catheter, subset = c(13, 6, 3, 12, 4, 
        11, 1, 14, 8, 10, 2))
Mantel-Haenszel OR =0.56    95% CI ( 0.37, 0.84 )
Test for heterogeneity: X^2( 9 ) = 5.32 ( p-value 0.8056 )
Fixed effects ( Mantel-Haenszel ) meta-analysis
Call: meta.MH(ntrt = n.trt, nctrl = n.ctrl, ptrt = inf.trt, pctrl = inf.ctrl, 
    names = Name, data = catheter, subset = c(13, 6, 3, 12, 4, 
        11, 1, 14, 8, 10, 2))
------------------------------------
             OR (lower  95% upper)
Tennenberg 0.57    0.19       1.75
Maki       0.20    0.04       0.94
Hannan     0.60    0.18       2.00
Bach(b)     NaN    0.00        NaN
Heard      0.86    0.26       2.89
Collins    0.35    0.04       3.16
Ciresi     0.95    0.43       2.10
Pemberton  0.82    0.13       5.24
Ramsay     0.23    0.03       2.11
Trazzera   0.63    0.17       2.42
George     0.25    0.02       2.50
------------------------------------
Mantel-Haenszel OR =0.56 95% CI ( 0.37,0.84 )
Test for heterogeneity: X^2( 9 ) = 5.32 ( p-value 0.8056 )

rmeta documentation built on May 2, 2019, 1:10 p.m.