Update an existing meta-analysis object.
# S3 method for meta
update(
object,
data = object$data,
subset,
studlab,
exclude,
cluster,
rho = object$rho,
cycles,
method,
sm = object$sm,
incr = object$incr,
method.incr = object$method.incr,
allstudies = object$allstudies,
incr.e,
incr.c,
incr.event,
MH.exact = object$MH.exact,
RR.Cochrane = object$RR.Cochrane,
Q.Cochrane = object$Q.Cochrane,
model.glmm = object$model.glmm,
level = object$level,
level.ma = object$level.ma,
common = object$common,
random = object$random,
overall = object$overall,
overall.hetstat = object$overall.hetstat,
method.random.ci = object$method.random.ci,
adhoc.hakn.ci = object$adhoc.hakn.ci,
method.predict = object$method.predict,
adhoc.hakn.pi = object$adhoc.hakn.pi,
seed.predict = object$seed.predict,
method.tau = object$method.tau,
method.tau.ci = object$method.tau.ci,
level.hetstat = object$level.hetstat,
tau.preset = object$tau.preset,
TE.tau = object$TE.tau,
tau.common = object$tau.common,
detail.tau = object$detail.tau,
method.I2 = object$method.I2,
prediction = object$prediction,
level.predict = object$level.predict,
null.effect = object$null.effect,
method.bias = object$method.bias,
backtransf = object$backtransf,
func.backtransf = object$func.backtransf,
args.backtransf = object$args.backtransf,
pscale = object$pscale,
irscale = object$irscale,
irunit = object$irunit,
text.common = object$text.common,
text.random = object$text.random,
text.predict = object$text.predict,
text.w.common = object$text.w.common,
text.w.random = object$text.w.random,
title = object$title,
complab = object$complab,
outclab = object$outclab,
label.e = object$label.e,
label.c = object$label.c,
label.left = object$label.left,
label.right = object$label.right,
col.label.left = object$col.label.left,
col.label.right = object$col.label.right,
n.e = object$n.e,
n.c = object$n.c,
method.mean = object$method.mean,
method.sd = object$method.sd,
approx.mean.e = object$approx.mean.e,
approx.mean.c = object$approx.mean.c,
approx.sd.e = object$approx.sd.e,
approx.sd.c = object$approx.sd.c,
approx.mean = object$approx.mean,
approx.sd = object$approx.sd,
approx.TE = object$approx.TE,
approx.seTE = object$approx.seTE,
pooledvar = object$pooledvar,
method.smd = object$method.smd,
sd.glass = object$sd.glass,
exact.smd = object$exact.smd,
method.ci = object$method.ci,
subgroup,
subgroup.name = object$subgroup.name,
print.subgroup.name = object$print.subgroup.name,
sep.subgroup = object$sep.subgroup,
test.subgroup = object$test.subgroup,
prediction.subgroup = object$prediction.subgroup,
seed.predict.subgroup = object$seed.predict.subgroup,
byvar,
id,
print.CMH = object$print.CMH,
keepdata = TRUE,
left = object$left,
ma.common = object$ma.common,
type = object$type,
n.iter.max = object$n.iter.max,
warn = FALSE,
warn.deprecated = gs("warn.deprecated"),
verbose = FALSE,
control = object$control,
...
)An object of class "meta" and "metabin",
"metacont", "metacor", "metainc",
"metagen", "metamean", "metaprop", or
"metarate" (see meta-object).
An object of class meta.
Dataset.
Subset.
Study label.
An optional vector specifying studies to exclude from meta-analysis, however, to include in printouts and forest plots.
An optional vector specifying which estimates come from the same cluster resulting in the use of a three-level meta-analysis model.
Assumed correlation of estimates within a cluster.
A numeric vector with the number of cycles per patient / study
in n-of-1 trials (see metagen).
A character string indicating which method is to be
used for pooling of studies (see metabin,
metainc, metaprop and
metarate).
A character string indicating which summary measure is used for pooling.
Information on increment added to cell frequencies of
studies with zero cell counts (see metabin,
metainc, metaprop and
metarate).
A character string indicating which continuity
correction method should be used (see metabin,
metainc, metaprop and
metarate).
A logical indicating if studies with zero or all
events in both groups are to be included in the meta-analysis
(applies only to metabin object with sm
equal to "RR" or "OR").
Continuity correction in experimental group (see
metabin and metainc).
Continuity correction in control group (see
metabin and metainc).
Continuity correction (see
metaprop and metarate).
A logical indicating if incr is not to be
added to all cell frequencies for studies with a zero cell count
to calculate the pooled estimate based on the Mantel-Haenszel
method (applies only to metabin object).
A logical indicating which method to use as
continuity correction for the risk ratio (see
metabin).
A logical indicating which method to use to
calculate the heterogeneity statistic Q (see
metabin).
A character string indicating which GLMM model
should be used (see metabin and
metainc).
The level used to calculate confidence intervals for individual studies.
The level used to calculate confidence intervals for meta-analysis estimates.
A logical indicating whether a common effect meta-analysis should be conducted.
A logical indicating whether a random effects meta-analysis should be conducted.
A logical indicating whether overall summaries should be reported. This argument is useful in a meta-analysis with subgroups if overall results should not be reported.
A logical value indicating whether to print heterogeneity measures for overall treatment comparisons. This argument is useful in a meta-analysis with subgroups if heterogeneity statistics should only be printed on subgroup level.
A character string indicating which method
is used to calculate confidence interval and test statistic for
random effects estimate (see meta-package).
A character string indicating whether an
ad hoc variance correction should be applied in the case
of an arbitrarily small Hartung-Knapp variance estimate (see
meta-package).
A character string indicating which method is
used to calculate a prediction interval (see
meta-package).
A character string indicating whether an
ad hoc variance correction should be applied for
prediction interval (see meta-package).
A numeric value used as seed to calculate
bootstrap prediction interval (see meta-package).
A character string indicating which method is
used to estimate the between-study variance \(\tau^2\) and its
square root \(\tau\) (see meta-package).
A character string indicating which method is
used to estimate the confidence interval of \(\tau^2\) and
\(\tau\) (see meta-package).
The level used to calculate confidence intervals for heterogeneity statistics.
Prespecified value for the square root of the between-study variance \(\tau^2\).
Overall treatment effect used to estimate the between-study variance tau-squared.
A logical indicating whether tau-squared should be the same across subgroups.
Detail on between-study variance estimate.
A character string indicating which method is
used to estimate the heterogeneity statistic I\(^2\). Either
"Q" or "tau2", can be abbreviated
(see meta-package).
A logical indicating whether a prediction interval should be printed.
The level used to calculate prediction interval for a new study.
A numeric value specifying the effect under the null hypothesis.
A character string indicating which test for
funnel plot asymmetry is to be used, can be abbreviated. See
function metabias.
A logical indicating whether results should be
back transformed in printouts and plots. If backtransf =
TRUE, results for sm = "OR" are printed as odds ratios
rather than log odds ratios and results for sm = "ZCOR"
are printed as correlations rather than Fisher's z transformed
correlations, for example.
A function used to back-transform results
(see metagen).
An optional list to provide additional
arguments to func.backtransf (see metagen).
A numeric giving scaling factor for printing of
single event probabilities or risk differences, i.e. if argument
sm is equal to "PLOGIT", "PLN",
"PRAW", "PAS", "PFT", or "RD".
A numeric defining a scaling factor for printing of
single incidence rates or incidence rate differences, i.e. if
argument sm is equal to "IR", "IRLN",
"IRS", "IRFT", or "IRD".
A character specifying the time unit used to calculate rates, e.g. person-years.
A character string used in printouts and forest plot to label the pooled common effect estimate.
A character string used in printouts and forest plot to label the pooled random effects estimate.
A character string used in printouts and forest plot to label the prediction interval.
A character string used to label weights of common effect model.
A character string used to label weights of random effects model.
Title of meta-analysis / systematic review.
Comparison label.
Outcome label.
Label for experimental group.
Label for control group.
Graph label on left side of null effect in forest plot.
Graph label on right side of null effect in forest plot.
The colour of the graph label on the left side of the null effect.
The colour of the graph label on the right side of the null effect.
Number of observations in experimental group (only for
metagen or metainc object).
Number of observations in control group (only for
metagen or metainc object).
A character string indicating which method to
use to approximate the mean from the median and other statistics
(see metacont and metamean).
A character string indicating which method to use
to approximate the standard deviation from sample size, median,
interquartile range and range (see metacont and
metamean).
Approximation method to estimate means in
experimental group (see metacont).
Approximation method to estimate means in
control group (see metacont).
Approximation method to estimate standard
deviations in experimental group (see metacont).
Approximation method to estimate standard
deviations in control group (see metacont).
Approximation method to estimate means (see
metamean).
Approximation method to estimate standard
deviations (see metamean).
Approximation method to estimate treatment
estimate (see metagen).
Approximation method to estimate standard error
(see metagen).
A logical indicating if a pooled variance should
be used for the mean difference or ratio of means (see
metacont).
A character string indicating which method is
used to estimate the standardised mean difference (see
metacont).
A character string indicating which standard
deviation is used in the denominator for Glass' method to
estimate the standardised mean difference (only for metacont
object with sm = "SMD"). Either "control" using the
standard deviation in the control group (sd.c) or
"experimental" using the standard deviation in the
experimental group (sd.e), can be abbreviated.
A logical indicating whether exact formulae should be used in estimation of the standardised mean difference and its standard error.
A character string indicating which method is used
to calculate confidence intervals for individual studies. Either
"z", "t", "WS", "WSCC", "AC",
"SA", "SACC", "NAsm", or "Poisson",
can be abbreviated. See functions metacont,
metaprop and metarate.
An optional vector to conduct a meta-analysis with subgroups.
A character string with a name for the subgroup variable.
A logical indicating whether the name of the subgroup variable should be printed in front of the group labels.
A character string defining the separator between name of subgroup variable and subgroup label.
A logical value indicating whether to print results of test for subgroup differences.
A logical indicating whether prediction intervals should be printed for subgroups.
A numeric vector providing seeds to calculate bootstrap prediction intervals within subgroups. Must be of same length as the number of subgroups.
Deprecated argument (replaced by 'subgroup').
Deprecated argument (replaced by 'cluster').
A logical indicating whether result of the Cochran-Mantel-Haenszel test for overall effect should be printed.
A logical indicating whether original data (set) should be kept in meta object.
A logical indicating whether studies are supposed to be
missing on the left or right side of the funnel plot. If NULL,
the linear regression test for funnel plot symmetry (i.e.,
function metabias(..., method = "linreg")) is used to
determine whether studies are missing on the left or right side.
A logical indicating whether a common effect or random effects model is used to estimate the number of missing studies.
A character indicating which method is used to estimate
the number of missing studies. Either "L" or "R".
Maximum number of iterations to estimate number of missing studies.
A logical indicating whether warnings should be printed
(e.g., if incr is added to studies with zero cell
frequencies).
A logical indicating whether warnings should be printed if deprecated arguments are used.
A logical indicating whether to print information on updates of older meta versions.
An optional list to control the iterative process to
estimate the between-study variance \(\tau^2\). This argument
is passed on to rma.uni or
rma.glmm, respectively.
Additional arguments (ignored at the moment).
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
Wrapper function to update an existing meta-analysis object which
was created with R function metabin,
metacont, metacor,
metagen, metainc,
metamean, metaprop, or
metarate. More details on function arguments are
available in help files of respective R functions.
This function can also be used for objects of class 'trimfill', 'metacum', and 'metainf'.
metabin, metacont,
metacor, metagen,
metainc, metamean,
metaprop, metarate
data(Fleiss1993cont)
m1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
data = Fleiss1993cont, studlab = paste(study, year), sm = "SMD")
m1
# Change summary measure (from 'SMD' to 'MD')
#
update(m1, sm = "MD")
# Restrict analysis to subset of studies
#
update(m1, subset = 1:2)
# Use different levels for confidence intervals
#
m2 <- update(m1, level = 0.66, level.ma = 0.99)
print(m2, digits = 2)
forest(m2)
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