meta.## S3 method for class 'meta':
print(x, sortvar,
comb.fixed=x$comb.fixed,
comb.random=x$comb.random,
prediction=x$prediction,
details=FALSE, ma=TRUE, logscale=FALSE, digits=max(4, .Options$digits - 3), ...)## S3 method for class 'metabias':
print(x, ...)
## S3 method for class 'meta':
summary(object,
comb.fixed=object$comb.fixed, comb.random=object$comb.random,
prediction=object$prediction,
bylab=object$bylab, print.byvar=object$print.byvar,
bystud=FALSE, print.CMH=object$print.CMH,
warn=object$warn, ...)
## S3 method for class 'summary.meta':
print(x, digits = max(3, .Options$digits - 3),
comb.fixed=x$comb.fixed, comb.random=x$comb.random,
prediction=x$prediction,
print.byvar=x$print.byvar, print.CMH=x$print.CMH,
header=TRUE, logscale=FALSE,
bylab.nchar=35, ...)
cilayout(bracket="[", separator="; ")
meta, metabias, or
summary.meta.meta.x$TE).print.default.summary.meta in connection with metacum or
metainf should result in a warning.summary.meta with the
following elements:byvar is not missing.byvar is not missing.byvar
is not missing.byvar
is not missing.byvar is not missing.byvar is not missing.byvar is not missing.byvar is not missing.byvar is not missing.byvar is not
missing.update.meta (or directly in R
functions metabin, metacont,
metagen, metacor, and
metaprop). Review Manager 5 (RevMan 5) is the current software used for
preparing and maintaining Cochrane Reviews
(read.rm5. If a meta-analysis is then
conducted using function metacr, information on subgroups is
available in R (components byvar, bylab, and
print.byvar, byvar in an object of class
"meta"). Accordingly, by using function metacr there is
no need to define subgroups in order to redo the statistical analysis
conducted in the Cochrane review.
Note, for an object of type metaprop, exact binomial
confidence intervals are calculated for individual study results
using the R function binom.test
internally. Accordingly, list elements TE, lower and
upper in element study correspond to proportions and
exact confidence limits on the natural scale (irrespective of the
transformation used in meta-analysis). Contrary, meta-analysis
results are transformed as defined by argument sm, i.e. list
elements TE, lower and upper in elements
fixed, random, within.fixed and
within.random.
R function cilayout can be utilised to change the layout to print
confidence intervals (both in printout from print.meta and
print.summary.meta function as well as in forest plots). The default
layout is "[lower; upper]". Another popular layout is "(lower -
upper)" which is used throughout an R session by using R command
cilayout("(", "- ").
Higgins JPT & Thompson SG (2002), Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539--1558.
update.meta, metabin, metacont, metagendata(Fleiss93cont)
meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, data=Fleiss93cont, sm="SMD")
summary(meta1)
summary(update(meta1, byvar=c(1,2,1,1,2), bylab="group"))Run the code above in your browser using DataLab