metacr  R Documentation 
Wrapper function to perform metaanalysis for a single outcome of a Cochrane Intervention review.
metacr(
x,
comp.no = 1,
outcome.no = 1,
method,
sm,
level = gs("level"),
common,
random,
prediction = gs("prediction")  !missing(method.predict),
method.tau = "DL",
method.tau.ci = gs("method.tau.ci"),
tau.common = FALSE,
level.ma = gs("level.ma"),
method.random.ci = "classic",
adhoc.hakn.ci = gs("adhoc.hakn.ci"),
level.predict = gs("level.predict"),
method.predict = gs("method.predict"),
adhoc.hakn.pi = gs("adhoc.hakn.pi"),
seed.predict = NULL,
Q.Cochrane,
swap.events,
logscale,
backtransf = gs("backtransf"),
test.subgroup,
prediction.subgroup = gs("prediction.subgroup"),
seed.predict.subgroup = NULL,
text.common = gs("text.common"),
text.random = gs("text.random"),
text.predict = gs("text.predict"),
text.w.common = gs("text.w.common"),
text.w.random = gs("text.w.random"),
title,
complab,
outclab,
keepdata = gs("keepdata"),
warn = FALSE,
warn.deprecated = gs("warn.deprecated"),
...
)
x 
An object of class 
comp.no 
Comparison number. 
outcome.no 
Outcome number. 
method 
A character string indicating which method is to be
used for pooling of studies. One of 
sm 
A character string indicating which summary measure
( 
level 
The level used to calculate confidence intervals for individual studies. 
common 
A logical indicating whether a common effect metaanalysis should be conducted. 
random 
A logical indicating whether a random effects metaanalysis should be conducted. 
prediction 
A logical indicating whether a prediction interval should be printed. 
method.tau 
A character string indicating which method is
used to estimate the betweenstudy variance 
method.tau.ci 
A character string indicating which method is
used to estimate the confidence interval of 
tau.common 
A logical indicating whether tausquared should be the same across subgroups. 
level.ma 
The level used to calculate confidence intervals for metaanalysis estimates. 
method.random.ci 
A character string indicating which method
is used to calculate confidence interval and test statistic for
random effects estimate (see 
adhoc.hakn.ci 
A character string indicating whether an
ad hoc variance correction should be applied in the case
of an arbitrarily small HartungKnapp variance estimate (see

level.predict 
The level used to calculate prediction interval for a new study. 
method.predict 
A character string indicating which method is
used to calculate a prediction interval (see

adhoc.hakn.pi 
A character string indicating whether an
ad hoc variance correction should be applied for
prediction interval (see 
seed.predict 
A numeric value used as seed to calculate
bootstrap prediction interval (see 
Q.Cochrane 
A logical indicating if the MantelHaenszel estimate is used in the calculation of the heterogeneity statistic Q which is implemented in RevMan 5. 
swap.events 
A logical indicating whether events and nonevents should be interchanged. 
logscale 
A logical indicating whether effect estimates are entered on logscale. 
backtransf 
A logical indicating whether results should be
back transformed in printouts and plots. If

test.subgroup 
A logical value indicating whether to print results of test for subgroup differences. 
prediction.subgroup 
A logical indicating whether prediction intervals should be printed for subgroups. 
seed.predict.subgroup 
A numeric vector providing seeds to calculate bootstrap prediction intervals within subgroups. Must be of same length as the number of subgroups. 
text.common 
A character string used in printouts and forest plot to label the pooled common effect estimate. 
text.random 
A character string used in printouts and forest plot to label the pooled random effects estimate. 
text.predict 
A character string used in printouts and forest plot to label the prediction interval. 
text.w.common 
A character string used to label weights of common effect model. 
text.w.random 
A character string used to label weights of random effects model. 
title 
Title of metaanalysis / systematic review. 
complab 
Comparison label. 
outclab 
Outcome label. 
keepdata 
A logical indicating whether original data (set) should be kept in meta object. 
warn 
A logical indicating whether warnings should be printed
(e.g., if 
warn.deprecated 
A logical indicating whether warnings should be printed if deprecated arguments are used. 
... 
Additional arguments (to catch deprecated arguments). 
Cochrane intervention reviews are based on the comparison of two interventions. Each Cochrane intervention review can have a variable number of comparisons. For each comparison, a variable number of outcomes can be define. For each outcome, a seperate metaanalysis is conducted. Review Manager 5 (RevMan 5) was the software used for preparing and maintaining Cochrane Reviews (https://training.cochrane.org/onlinelearning/coresoftware/revman).
This wrapper function can be used to perform metaanalysis for a
single outcome of a Cochrane intervention review. Internally, R
functions metabin
, metacont
, and
metagen
are called  depending on the definition of
the outcome in RevMan 5.
Note, it is recommended to choose the RevMan 5 settings before
executing metacr
, i.e., settings.meta("revman5")
.
An object of class "meta"
and  depending on outcome type
utilised in Cochrane intervention review for selected outcome 
"metabin"
, "metacont"
, or "metagen"
with
corresponding generic functions (see metaobject
).
Guido Schwarzer guido.schwarzer@uniklinikfreiburg.de
Review Manager (RevMan) [Computer program]. Version 5.4. The Cochrane Collaboration, 2020
metapackage
, metabin
,
metacont
, metagen
,
read.rm5
, settings.meta
# Locate export data file "Fleiss1993_CR.csv"
# in subdirectory of package "meta"
#
filename < system.file("extdata", "Fleiss1993_CR.csv", package = "meta")
#
Fleiss1993_CR < read.rm5(filename)
# Choose RevMan 5 settings and store old settings
#
oldset < settings.meta("revman5", quietly = FALSE)
# Same result as R command example(Fleiss1993bin)
#
metacr(Fleiss1993_CR)
# Same result as R command example(Fleiss1993cont)
#
metacr(Fleiss1993_CR, 1, 2)
forest(metacr(Fleiss1993_CR, 1, 2))
# Change summary measure to RR
#
m1 < metacr(Fleiss1993_CR)
update(m1, sm="RR")
# Use old settings
#
settings.meta(oldset)
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