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Conduct a test for funnel plot asymmetry for all outcomes in a Cochrane review
# S3 method for rm5
metabias(
x,
comp.no,
outcome.no,
method.bias = "linreg",
method.bias.binary = method.bias,
method.bias.or = "score",
k.min = 10,
...
)
An object of class rm5
.
Comparison number.
Outcome number.
A character string indicating which test for
small-study effects is to be used for all outcomes. Either
"rank"
, "linreg"
, or "mm"
, can be
abbreviated. See function metabias
A character string indicating which test
is to be used for binary outcomes. Either "rank"
,
"linreg"
, "mm"
, "count"
, "score"
, or
"peters"
, can be abbreviated. See function
metabias
A character string indicating which test is
to be used for binary outcomes with odds ratio as summary
measure. Either "rank"
, "linreg"
, "mm"
,
"count"
, "score"
, or "peters"
, can be
abbreviated. See function metabias
Minimum number of studies to perform test for small-study effects.
Additional arguments (ignored at the moment)
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
This function can be used to conduct a test for funnel plot asymmetry for all or selected meta-analyses in a Cochrane Review.
Review Manager 5 (RevMan 5) was the software used for preparing and
maintaining Cochrane Reviews
(https://training.cochrane.org/online-learning/core-software/revman).
In RevMan 5, subgroup analyses can be defined and data from a
Cochrane review can be imported to R using the function
read.rm5
.
The R function metacr
is called internally.
Higgins, J.P.T and S. Green (2011): Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [Updated March 2011]. The Cochrane Library: http://www.cochrane-handbook.org/
metabias
, metacr
,
read.rm5
, summary.rm5
# Locate export data file "Fleiss1993_CR.csv" in sub-directory of
# package "meta"
#
filename <- system.file("extdata", "Fleiss1993_CR.csv", package = "meta")
Fleiss1993_CR <- read.rm5(filename)
# Print results for all tests of small-study effects
#
metabias(Fleiss1993_CR, k.min = 5)
# Print result of test of small-study effects for second outcome in
# first comparison
#
metabias(Fleiss1993_CR, comp.no = 1, outcome.no = 2, k.min = 5)
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