Update an existing meta-analysis object.
# S3 method for meta
update(object,
data=object$data, subset=object$subset,
studlab=object$data$.studlab,
exclude=object$data$.exclude,
method=object$method, sm=object$sm,
incr, allincr=object$allincr,
addincr=object$addincr, allstudies=object$allstudies,
MH.exact=object$MH.exact, RR.cochrane=object$RR.cochrane,
model.glmm = object$model.glmm,
level=object$level, level.comb=object$level.comb,
comb.fixed=object$comb.fixed, comb.random=object$comb.random,
hakn=object$hakn, method.tau=object$method.tau,
tau.preset=object$tau.preset,
TE.tau=object$TE.tau, tau.common=object$tau.common,
prediction=object$prediction, level.predict=object$level.predict,
null.effect=object$null.effect,
method.bias=object$method.bias, backtransf = object$backtransf,
pscale = object$pscale,
irscale = object$irscale, irunit = object$irunit,
title=object$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,
n.e=object$n.e, n.c=object$n.c,
pooledvar=object$pooledvar, method.smd=object$method.smd,
sd.glass=object$sd.glass, exact.smd=object$exact.smd,
method.ci=object$method.ci,
byvar=object$byvar, bylab=object$bylab, print.byvar=object$print.byvar,
byseparator = object$byseparator,
print.CMH=object$print.CMH, keepdata=TRUE,
left=object$left, ma.fixed=object$ma.fixed,
type=object$type, n.iter.max=object$n.iter.max,
warn=object$warn, ...)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.
A character string indicating which summary measure is used for pooling.
Either a numerical value or vector which can be added to
each cell frequency for studies with a zero cell count or the
character string "TA" which stands for treatment arm
continuity correction.
A logical indicating if incr is added to each
cell frequency of all studies if at least one study has a zero
cell count. If FALSE (default), incr is added only to each
cell frequency of studies with a zero cell count.
A logical indicating if incr is added to each cell
frequency of all studies irrespective of zero cell counts.
A logical indicating if studies with zero or all
events in both groups are to be included in the meta-analysis
(applies only if sm is equal to "RR" or
"OR").
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.
A logical indicating if 2*incr instead of
1*incr is to be added to n.e and n.c in the
calculation of the risk ratio (i.e., sm="RR") for studies
with a zero cell. This is used in RevMan 5, the
Cochrane Collaboration's program for preparing and maintaining
Cochrane reviews.
A character string indicating which GLMM model should be used.
The level used to calculate confidence intervals for individual studies.
The level used to calculate confidence intervals for pooled estimates.
A logical indicating whether a fixed effect meta-analysis should be conducted.
A logical indicating whether a random effects meta-analysis should be conducted.
A logical indicating whether the method by Hartung and Knapp should be used to adjust test statistics and confidence intervals.
A character string indicating which method is used
to estimate the between-study variance \(\tau^2\). Either
"DL", "PM", "REML", "ML", "HS",
"SJ", "HE", or "EB", can be abbreviated. See
function metagen.
Prespecified value for the square-root of the between-study variance \(\tau^2\).
Overall treatment effect used to estimate the between-study variance \(\tau^2\).
A logical indicating whether tau-squared should be the same across subgroups.
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. Either "rank",
"linreg", "mm", "count", "score", or
"peters", 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 numeric giving scaling factor for printing of single
event probabilities, i.e. if argument sm is equal to
"PLOGIT", "PLN", "PRAW", "PAS", or
"PFT".
A numeric defining a scaling factor for printing of
rates, i.e. if argument sm is equal to "IR",
"IRLN", "IRS", or "IRFT".
A character specifying the time unit used to calculate rates, e.g. person-years.
Title of meta-analysis / systematic review.
Comparison label.
Outcome label.
Label for experimental group.
Label for control group.
Graph label on left side of forest plot.
Graph label on right side of forest plot.
Number of observations in experimental group. (only for metagen object)
Number of observations in control group. (only for metagen object)
A logical indicating if a pooled variance should be
used for the mean difference (only for metacont object with
sm="MD").
A character string indicating which method is used
to estimate the standardised mean difference (only for metacont
object with sm="SMD"). Either "Hedges" for Hedges' g
(default), "Cohen" for Cohen's d, or "Glass" for
Glass' delta, can be abbreviated.
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
"CP", "WS", "WSCC", "AC",
"SA",, "SACC", or "NAsm", can be
abbreviated. See function metaprop.
An optional vector containing grouping information (must
be of same length as event.e).
A character string with a label for the grouping variable.
A logical indicating whether the name of the grouping variable should be printed in front of the group labels.
A character string defining the separator between label and levels of grouping variable.
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 fixed 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).
Additional arguments (ignored at the moment).
An object of class "meta" and "metabin",
"metacont", "metacor", "metainc",
"metagen", "metamean", "metaprop", or
"metarate".
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
# NOT RUN {
data(Fleiss93cont)
meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c,
data=Fleiss93cont, sm="SMD", studlab=study)
meta1
# Change summary measure (from 'SMD' to 'MD')
#
update(meta1, sm="MD")
# Restrict analysis to subset of studies
#
update(meta1, subset=1:2)
# Use different levels for confidence intervals
#
meta2 <- update(meta1, level=0.66, level.comb=0.99)
print(meta2, digits=2)
forest(meta2)
# }
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