meta.DSL {rmeta}

Random effects (DerSimonian-Laird) meta-analysis

Description

Computes the individual odds ratios or relative risks, the summary, the random effects variance, 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. Studies with zero or infinite odds ratio are omitted, as their variance cannot be calculated sensibly.

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.DSL(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.DSL'
summary(object, conf.level=NULL, ...)
## S3 method for class 'meta.DSL'
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

conf.level

Coverage for confidence intervals

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.DSL object

summary

Plot the summary odds ratio?

summlabel

Label for the summary odds ratio

colors

see meta.colors

xlab

x-axis label, default is based on statistic

...

further arguments to be passed from or to methods.

Value

An object of class meta.DSL with print, plot, funnelplot and summary methods.

Author(s)

Thomas Lumley

See Also

plot,par,meta.MH,funnelplot

Examples

data(catheter)
b <- meta.DSL(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))
b
summary(b)
plot(b)
e <- meta.DSL(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))
e
summary(e)
##tasteless
plot(e, colors=meta.colors(summary="green",lines="purple",box="orange"))