NEWS
meta 8.1-0
Bug fixes
-
forest.meta():
- consider setting for list element 'null.effect' for metamean(), metaprop()
and metarate() objects to fix
issue #67
-
update.meta():
- consider setting for list element 'rho' for metabin(), metacor(),
metainc(), metamean(), metaprop(), metarate()
User-visible changes
-
metabin(), metainc():
- new arguments 'incr.e' and 'incr.c' for user-specified continuity correction
- do not warn about continuity correction for generalized linear mixed models
and penalised logistic regression
- arguments 'addincr' and 'allincr' in argument '...' ignored
-
pairwise():
- new argument 'sm' to specify summary measure (this argument was previously
available via argument '...')
- argument 'method' can be any admissible value for metabin(), metacont(),
metacont(), or metagen()
- argument 'n' considered for count data
-
metacr():
- new arguments 'label.left' and 'label.rigth' to fix
issue #66
-
metabin(), metacont(), metacor(), metainc(), metamean(), metaprop(),
metarate(), update.meta():
- new argument 'detail.tau'
Internal changes
meta 8.0-2 (2025-01-21)
Bug fixes
-
update.meta():
-
pairwise():
- fix bug if R package netmeta is not installed
-
metabin():
- fix bug for penalised logistic regression of single study
-
metaprop():
- use p2logit() to calculate the transformed null effect
-
metaprop(), metarate():
- for random intercept logistic regression model consider input for
argument 'null.effect' instead of using 0
User-visible changes
meta 8.0-1 (2024-10-31)
Revise web links
meta 8.0-0
Major changes
-
By default, prediction intervals are based on k - 1 instead of k - 2
degrees of freedom
(Veroniki et al., 2019, RSM) where k
corresponds to the number of studies in the meta-analysis;
see help("meta-package") for more details on methods to calculate prediction
intervals
-
Meta-analysis of n-of-1 trials implemented
(Senn, 2024, Trials)
-
Logistic regression with penalised likelihood implemented for meta-analysis
of rare events
(Evrenoglou et al., 2022, Stat Med)
-
I2 statistic can be calculated from between-study variance instead of
Q statistic (new argument 'method.I2')
-
R functions pairwise() and subset.pairwise() moved from R package
netmeta to meta
-
R function pairwise() can be used with dose-response data
-
Information on colour of labels on left and right side of null effect in
forest plots can be stored in meta-analysis object
-
In forest plots,
- the heterogeneity statistic Q, its p-value, and the I2 statistic are
printed with the same number of digits as in printouts
- the text for subgroups is printed in "black" instead of "darkgray"
(argument 'col.subgroup')
-
Level of confidence intervals for heterogeneity statistics can be specified
by the user (argument 'level.hetstat'); in previous version of R package
meta confidence intervals for tau2 and tau were always 95%-CIs while
confidence intervals for I2 and H were based on the value for argument
'level.ma'
-
First argument to R functions metabin(), metacont(), metagen(), and metainc()
can be a pairwise() object
-
In funnel.meta(), arguments 'pch', 'cex', and 'cex.studlab' can be of same
length as the number of studies
-
New auxiliary function setvals() to easily define the input for arguments
'pch', 'cex', 'col', 'bg', 'text', and 'cex.studlab' in funnel.meta();
e.g., to use different colours for subgroups
-
R package
brglm2
added to suggested packages to fit penalized logistic regression for
meta-analysis of rare events
(Evrenoglou et al., 2022, Stat Med)
-
Print a warning message if deprecated arguments are used, e.g., 'comb.fixed'
or 'fixed' instead of 'common'
-
The command settings.meta("meta7") can be used to get the meta-analysis
settings from meta, version 7.0-0
User-visible changes
-
metabin(), metacont(), metacor(), metacr(), metagen(), metainc(), metamean(),
metaprop(), metarate(), update.meta():
- new argument 'method.I2' to choose method to calculate I2 statistic
- new argument 'level.hetstat' to specify level of confidence intervals for
heterogeneity statistics
- new arguments 'col.label.left' and 'col.label.right' to define colour of
labels used in forest plots on left and right side of null effect
-
metagen():
- new argument 'cycles' for meta-analysis of n-of-1 trials
-
metabin():
- fit penalised logistic regression if argument 'sm = "LRP"'
-
Do not print the start-up message concerning older version of R package
meta for readers of 'Meta-Analysis with R (Use R!)'
-
funnel.meta():
- new argument 'type' to create a contour-enhanced funnel plot with default
settings
- argument '...' passed on to plot.default(), e.g., to specify font family
-
print.summary.meta():
- new arguments 'digits.Q', 'digits.df', 'digits.pval.Q', 'digits.H',
'print.tau2.ci', 'print.tau.ci', 'print.Q', 'print.H', 'print.Rb', 'text.Rb'
-
pairwise():
- new arguments 'agent' and 'dose' to provide information for dose-response
data
- new argument 'varnames' to change variable names for effect estimate and
its standard error
-
bubble.metareg():
- argument 'backtransf = TRUE' is recognized for additional summary measures,
i.e., "PLOGIT", "PLN", "PAS", "IRLN", "IRS", "ZCOR"
-
settings.meta():
- default setting can be defined for 'print.I2.ci'
- additional settings, e.g., for R package netmeta, can be changed
Bug fixes
-
forest.meta():
- print "logVR" instead of "logVE" or "VE" for not back-transformed
vaccine efficacy / effectiveness (sm = "VE")
- additional check whether input for argument 'sortvar' is a function
(for example, using a variable 'order' resulted in an error due to the
R function order())
-
bubble.metareg():
- use of vector instead of single value for argument 'pch' resulted in wrong
order of plotting symbols
-
metagen():
- set list elements 'approx.TE' or 'approx.seTE' to NULL if no approximation
has been used
-
print.summary.meta():
- recognize the arguments 'scientific.pval', 'zero.pval', 'JAMA.pval'
-
runGLMM():
- use results of common effect model as fallback for error
"Cannot fit ML model" and print corresponding warning
-
pairwise():
- inconsistent values for Cohen's d if data was already provided in contrast
based format
- argument 'append = FALSE' didn't work
Internal changes
- metamean(): use mean value if median is not provided to approximate missing
standard deviation
meta 7.0-0 (2024-01-12)
Major changes
-
Vignettes added
-
R package metadat added to Depends (to access meta-analysis datasets)
-
R package robvis added to Suggests (for risk of bias assessment)
-
New functions rob(), barplot.rob() and traffic_light() for risk of
bias assessment (RoB)
-
New function read.cdir() to import Cochrane data package from
Cochrane review of interventions
-
New function blup.meta() to calculate best linear unbiased predictors (BLUPs)
-
New functions estimates(), estimates.meta(), and estimates.blup.meta() to
extract meta-analysis results
-
Lower and upper confidence interval limits of individual study
results stored as transformed limits for meta-analysis with single
proportions or rates (in previous versions of meta, CI limits were
back transformed for individual studies and not back transformed for
meta-analysis results)
-
Changes for forest plots:
- forest plot can be directly saved to a file using common graphics
device drivers (height of file is determined automatically)
- BMJ layout implemented (layout = "BMJ")
- details on meta-analysis methods can be shown in plot
- risk of bias assessment automatically added for meta-analyses with
RoB assessment
- point estimates can be plotted as circles or diamonds instead of
squares
- default settings for columns on left or right side of forest plot
can be defined in settings.meta()
- common effect and random effects confidence intervals and
prediction intervals are truncated if lower / upper limit is outside the
limits of the x-axis
-
New general setting "BMJ", i.e., R command settings.meta("BMJ"),
to print results according to BMJ style and formating checklist,
see, for example, BMJ
Medicine
-
R function metabind() can return both common effect and random
effects results as well as prediction intervals
-
Internal functions for (back) transformations made visible /
accessible to the user; see help("meta-transf")
-
Within-cluster correlation can be specified for three-level model
(by default, rho = 0)
-
Use approximate formulae for Hedges' g and Cohen's d for RevMan 5
settings; see help page of settings.meta()
-
Argument 'pscale' or 'irscale' could be used in principle with any
effect measure which is useful for user-specified summary measure in
metagen()
-
New R function plot.meta() which calls forest.meta() internally
-
Do not export the following R functions but rely on their generic functions:
- forest.meta(), funnel.meta(), labels.meta(), print.summary.meta(),
summary.meta(), update.meta()
User-visible changes
-
metabin(), metacont(), metacor(), metainc(), metamean(), metaprop(),
metarate(), update.meta():
- new argument 'rho' to specify within-cluster correlation in
three-level model
-
print.meta():
- show group sample sizes in printouts
- print confidence intervals based on t- and normal distribution for
metacont() or metamean() objects with a single study and argument
'method.ci = "t"'
- new argument 'print.Q' to suppress printing of heterogeneity
statistic Q and test of heterogeneity
- default for argument 'details.methods' can be defined using
settings.meta()
- do not print degrees of freedom for Hartung-Knapp or Kenward-Rogers
intervals if argument \code{overall = FALSE}
-
gs():
- first argument can be a character vector instead of a character string
to get the default setting of several arguments (which would be returned
as a list)
- new argument 'unname' to return named arguments (if unname = FALSE)
-
metamerge():
- can be used with object created with copas() or limitmeta() from R
package metasens as only input (which adds the respective
results to the standard meta-analysis object)
- arguments 'label1' and 'label2' can be used to provide defaults to
amend labels for common effect or random effects model, prediction
intervals and subgroups
- new arguments 'label1.common', 'label2.common', 'label1.random',
'label2.random', 'label1.predict', 'label2.predict',
'label1.subgroup', and 'label2.subgroup'
-
metaadd():
- argument 'data' can be a meta-analysis object created with R
package meta
- new arguments 'method.common', 'method.random', 'method.tau',
'method.random.ci', and 'method.predict'
-
metabind():
- new arguments 'common', 'random' and 'prediction' replacing
argument 'pooled'
-
forest.meta():
- new arguments 'file', 'width', 'rows.gr', 'func.gr', 'args.gr',
and 'dev.off' to directly store a forest plot in a file
- new arguments 'rob', 'rob.col', 'rob.symbols', 'rob.attach',
'rob.xpos', 'rob.legend', 'fs.rob', 'fs.rob.symbols', 'ff.rob',
'ff.rob.symbols', 'colgap.rob' and 'just.rob' for risk of bias
assessment
- new arguments 'details', 'fs.details' and 'ff.details' to add
details on meta-analytical methods
- point estimates can be plotted as circles instead of squares or
diamonds (arguments 'type.study', 'type.common', 'type.random',
'type.subgroup', 'type.subgroup.common', 'type.subgroup.random')
- new arguments 'col.circle' and 'col.circle.lines' to define the
colour of circles
- new argument 'digits.n' and 'digits.event' to specify the number
of significant digits for sample sizes and number of events
- justification of results for effect + confidence interval can be
specified by argument 'just' if argument 'layout = "RevMan5"'
-
settings.meta():
- new argument 'overall.hetstat' to specify whether to show
information on between-study heterogeneity
- new argument 'width' to specify width of graphics device
- new arguments 'print.tau2', 'print.tau2.ci', 'print.tau' and
'print.tau.ci' to specify whether to show (confidence intervals
for) tau^2 or tau in printouts
- new arguments 'leftcols', 'rightcols', 'leftlabs', 'rightlabs',
'label.e.attach' and 'label.c.attach' to changes defaults for
corresponding arguments in forest.meta()
-
bubble.meta():
- new arguments 'pscale' and 'irscale' added
-
metaprop(), metarate():
- list elements 'lower' and 'upper' contain the transformed lower
and upper confidence interval limits for individual studies
-
R functions for transformation:
- transf(), cor2z(), p2asin(), p2logit(), VE2logVR()
-
R functions for back transformation:
- backtransf(), asin2ir(), asin2p(), logit2p(), logVR2VE(), z2cor()
-
labels.meta():
- R function is not exported
Bug fixes
-
funnel.meta():
- automatically calculated limits on x-axis were to narrow for some
settings
-
metamean():
- argument 'null.effect' was ignored to calculate the test statistic
and p-value for individual studies (list elements 'statistic' and
'pval')
-
metabin():
- use continuity correction if sm = "VE"
-
metareg():
- error if input to argument 'formula' was the name of an R function
-
print.summary.meta():
- print correct backtransformed subgroup results for metabind objects
with metaprop objects with Freeman-Tukey transformation as input
Internal changes
-
New internal function gh() to determine height of graphics file
-
New internal function smlab() to determine the label for the summary measure
-
Use of vcalc() from R package metafor to calculate the
variance-covariance matrix in three-level model with within-cluster
correlation not equal to 0
-
funnel.meta(): list element of meta-analysis object can be directly
specified in arguments 'text', 'col' and 'bg', e.g., argument 'text
= studlab' to use study labels instead of plotting symbols
-
Input to chkchar() can be a numeric vector
-
settings.meta(): set defaults for arguments 'forest.tau2,' 'forest.tau',
'forest.I2', 'forest.Q', 'forest.pval.Q', and 'forest.Rb' for BMJ, JAMA
and RevMan5 layout
meta 6.5-0 (2023-06-07)
Major changes
-
In R function metamerge(), user can decide whether to keep or ignore
information from second meta-analysis on study weights and
heterogeneity statistics
-
New function metaadd() to add pooled results from external analysis
to meta-analysis object
-
Function update.meta() considers arguments 'method.mean' and 'method.sd'
-
Variables with group specific information can be merged into a
single variable in longarm()
-
Additional thresholds can be specified to plot vertical lines in
forest plots, e.g., to mark large, moderate and small effects
-
Baujat plot can be used to evaluate influence of studies on random
effects estimate
-
Seed can be specified in meta-analysis functions to calculate
reproducible bootstrap prediction intervals
User-visible changes
-
metamerge():
- new arguments 'common1', 'random1', 'prediction1', 'common2',
'random2', 'prediction2' to specify whether to keep common effect
results, random effects results or prediction interval from first
or second meta-analysis
- new arguments 'keep', 'keep.Q', 'keep.I2' and 'keep.w' to
determine whether additional information from second meta-analysis
should be kept
- new arguments 'common', 'random', 'prediction', 'overall' and
'overall.hetstat' to specify which results to print
- new arguments 'hetlabel1', 'hetlabel2', 'text.common1',
'text.common2', 'text.random1', 'text.random2', 'text.predict1'
and 'text.predict2' to label results from first or second
meta-analysis
-
longarm():
- new arguments 'id1' and 'id2' to specify last character(s) of
variable names with group specific information
Bug fixes
-
metabias():
- do not conduct test for funnel plot asymmetry for three-level
model (the test did not consider the cluster structure)
-
forest.meta():
- header line was concealed by equivalence region
- error if argument 'resid.hetstat = TRUE' was used for subgroup
meta-analysis without common between-study variance estimate in
subgroups (argument 'tau.common = FALSE' in meta-analysis
functions)
-
read.rm5():
- fix bug for error message "In gsub("\x80", "EUR", txt) : unable
to translate '<80>' to a wide string" due to change in default
settings in R function gsub()
User-visible changes
-
metabin(), metacont(), metacor(), metacr(), metainc(), metamean(),
metaprop(), metarate(), update.meta():
- new arguments 'seed.predict' and 'seed.predict.subgroup'
- print an error message if bootstrap prediction interval is
requested for three-level model
-
trimfill.default():
- new argument 'seed.predict'
-
baujat.meta():
-
forest.meta():
- arguments 'lower.equi' and 'upper.equi' can be numeric vectors
- new arguments 'fill.lower.equi' and 'fill.upper.equi' to specify
fill colour(s) for lower or upper limits
-
print.metabias():
- do not print the intercept and its standard error (nuisance parameter)
Internal changes
meta 6.2-1 (2023-02-28)
Bug fixes
-
forest.meta():
- correct order of cluster variable for three-level meta-analysis
with subgroups or use of argument 'sortvar'
-
metabin(), metacont(), metacor(), metainc(), metamean(), metaprop(),
metarate():
- recognise argument 'subset' for three-level meta-analysis
-
Ad hoc variance correction for Hartung-Knapp method was not used
for argument 'adhoc.hakn = "IQWiG6"' (bug was introduced in
meta, version 6.0-0)
User-visible changes
-
metacr():
- new argument 'Q.Cochrane'
-
metareg():
- using the regression formula as first unnamed argument will result
in an error not a warning
Internal changes
-
metagen(): check argument 'sm' for known summary measures in lower
case
-
setchar(): new arguments 'return.NULL' and 'nchar.equal'
-
New branch 'release' on GitHub starting with meta, version 6.2-1
meta 6.2-0 (2023-02-14)
Major changes
- New function trimfill.rm5() to conduct trim-and-fill method for all
or selected meta-analyses of a Cochrane review
User-visible changes
- nnt.meta(), print.nnt.meta():
Internal changes
-
Use generic functions metacum() for cumulative meta-analysis,
metainf() for leave-one-out meta-analysis and metareg() for
meta-regression
-
New internal function chksuitable() to check for suitable classes
meta 6.1-0 (2022-12-21)
Major changes
-
Meta-analysis of Vaccine Efficacy or Vaccine Effectiveness
implemented
-
For the generic inverse variance method,
- untransformed values can be provided for treatment estimates and
confidence limits, see argument 'transf'
- original confidence limits for individual studies kept if
arguments 'lower' and 'upper' are not missing
- standard error set to missing if lower and upper confidence limits
are identical (resulted in an error)
-
Methods by McGrath et.,
(2020) and Cai et.,
(2021) implemented to
approximate means and standard deviations from median and related
statistics
-
R package
estmeansd
added to suggested packages to provided methods by McGrath et.,
(2020) and Cai et.,
(2021)
-
Print header line in forest plots with JAMA or RevMan5 layout
Bug fixes
User-visible changes
-
All meta-analysis functions:
- print prediction interval(s) if argument 'method.predict' is not
missing
-
metabin, metagen(), metainc():
- argument 'sm = "VE"' can be used for meta-analysis of vaccine
efficacy or vaccine effectiveness
-
metagen(), settings.meta():
-
forest.meta():
- new argument 'header.line' to add header line
- new argument 'digits.TE' to specify number of digits for
transformed treatment estimates (list element 'TE')
- use more informative column labels for 'TE' and 'seTE'
-
metabin(), metainc(), metaprop() and metarate():
- for GLMMs, stop with error if argument 'adhoc.hakn.ci' or
'adhoc.hakn.pi' is unequal to ""
-
nnt.meta(), nnt.default():
- new argument 'small.values' to specify whether small treatment
effects indicate a beneficial or harmful effect
-
settings.meta():
- new argument 'digits.TE.forest' to set default for argument
'digits.TE' in forest.meta()
-
Print blank space before negative upper confidence interval limit if
separator is equal to "-"
-
New help page meta-sm summarising available summary measures
-
Help page of nnt() updated
-
Change maintainer's email address
Internal changes
-
New internal functions transf(), cor2z(), p2asin(), logVR2VE() and
VE2logVR()
-
chknumeric():
- new argument 'integer' to check for integer values
-
List element 'df.Q.b.random' with degrees of freedom for test of
subgroup differences under random effects model is a list instead of
a vector if more than one random effects method was used (argument
'method.random.ci')
-
Several changes for meta-analysis using generalised linear mixed or
three-level models
meta 6.0-0 (2022-09-17)
Major changes
-
Meta-analysis object can contain results of several common effect or
random effects methods, e.g., random effects meta-analysis with or
without Hartung-Knapp method
-
Kenward-Roger method implemented to estimate confidence or
prediction interval (Partlett & Riley,
2017)
-
Bootstrap approach implemented to calculate prediction interval
(Nagashima et al., 2019)
-
Rewrite of function metamerge() to merge pooled results of two
meta-analyses into a single meta-analysis object
-
Defaults for appearance of forest plots can be defined for the R
session
-
R package
pimeta
added to suggested packages in order to calculate bootstrap approach
for prediction interval
-
New argument 'method.random.ci' replaces argument 'hakn' to select
method to calculate confidence interval for random effects estimate
-
Major update of help pages:
- help page for meta-package revised; content with details in
meta-analysis functions moved to this help page
- new help page meta-object describing content of meta-analysis
functions; corresponding content moved from individual help pages
Bug fixes
-
forest.meta():
- do not print label for subgroups with no information to print,
e.g., if argument 'study.results = FALSE', for subgroups with only
one or no study contributing to pooled estimate in the subgroup
- do not show empty row before label on x-axis (argument 'xlab') if
argument 'label.left' or 'label.right' is provided for
meta-analysis without reference value (argument 'ref'), e.g.,
meta-analysis of single means or proportions
-
metareg():
- use Paule-Mandel estimator if used in meta-analysis (instead of
REML estimator)
User-visible changes
-
metabin(), metacont(), metacor(), metagen(), metainc(), metamean(),
metaprop() and metarate():
- argument 'hakn' replaced by 'method.random.ci'
- argument 'adhoc.hakn' replaced by 'adhoc.hakn.ci'
- new arguments 'method.predict' and 'adhoc.hakn.pi'
-
settings.meta():
- several new arguments added to define defaults for forest plots;
see printout of command settings.meta(print = TRUE)
-
forest.meta():
- argument 'col.by' has been renamed to 'col.subgroup',
- argument 'bysort' has been renamed to 'sort.subgroup'
-
trimfill.meta():
- arguments 'level', 'level.ma', 'method.random.ci', 'adhoc.hakn',
'method.tau', 'method.tau.ci', 'level.predict', and
'method.predict' removed
meta 5.5-0 (2022-07-11)
Major changes
-
Use term 'common effect model' instead of 'fixed effect model' in
the documentation and argument 'common' instead of 'fixed' to (not)
show results for common effect model
-
Three-level model implemented in all meta-analysis functions
-
For continuity corrections, new argument 'method.incr' replaces
arguments 'allincr' and 'addincr' for meta-analysis with binary
outcome or incidence rates
-
Exact Poisson confidence limits can be calculated for individual
studies in meta-analysis of single rates
-
Show information on statistical significance and between-study
heterogeneity in forest plots of cumulative or leave-one-out
meta-analysis
-
Calculate Cochran's Q directly in meta for classic inverse
variance meta-analysis (instead of taking it from metafor
package)
-
By default, do not print warnings for deprecated arguments; this can
be changed with command 'settings.meta(warn.deprecated = TRUE)'
Bug fixes
-
Use correct standard error for Cox and Snell's method in smd2or()
and or2smd()
-
Three-level model did not work if variable from dataset was
provided as input to argument 'id' in metacont()
-
Argument 'tau.common = TRUE' was ignored in subgroup analysis of
three-level model in metacont()
-
Argument 'level' was ignored in the calculation of confidence limits
for individual studies in metacont() and metamean() if argument
'method.ci = "t"'
-
Show correct studies in forest plot with subgroups and missing
treatment effects if argument 'allstudies = FALSE'
-
Show points in bubble plot of meta-regression with GLMM
User-visible changes
-
For three-level models,
- argument 'id' has been renamed to 'cluster'
- cluster variable is shown in forest plots
-
New arguments 'common' and 'cluster' in functions metabin(),
metacont(), metacor(), metagen(), metainc(), metamean(), metaprop()
and metarate()
-
New function subset.longarm() to select subset of a longarm object
-
New argument 'method.ci' in function metarate()
-
New argument 'method.ci.rate' in function settings.meta()
-
New argument 'method.incr' in functions metabin(), metainc(),
metaprop() and metarate()
-
print.summary.meta():
- for a single study and metabin() with method = "MH", sm = "RR" and
RR.Cochrane = FALSE, print results using a continuity correction
for sample sizes of 1x incr (individual study) and 2x incr
(meta-analysis of single study)
Internal changes
-
forest.meta():
- use meta:::formatN() instead of format() for formatting
- print study label "1" instead of "" for a single study
-
metarate():
- list elements 'lower' and 'upper' contain untransformed confidence
limits for individual studies
-
New internal function update_needed() to check whether update of
meta object is needed
-
metabin(), metacont(), metacor(), metagen(), metainc(), metamean(),
metaprop() and metarate():
- new list element 'k.TE' with number of estimable effects
meta 5.2-0 (2022-02-05)
Major changes
-
Forest plot for meta-analysis with subgroups:
- more flexible printing of subgroup results
- by default, do not show subgroup results (pooled estimates and
information on heterogeneity) for subgroups consisting of a single
study
-
Prediction intervals in subgroups can be shown independently of
prediction interval for overall meta-analysis in printouts and
forest plots
-
Bubble plot shows relative treatment effects on original scale
instead of log scale and reference line is shown
-
Trim and fill, limit meta-analysis and Copas selection model objects
can be used in function metabind()
-
New function longarm() to transform data from pairwise comparisons
to long arm-based format
-
New auxiliary function labels.meta() to create study labels for
forest plots in JAMA or Lancet layout
-
Printing of spaces in confidence intervals can be suppressed
-
Help page of forest.meta() updated
Bug fixes
-
Use correct standard error to calculate prediction interval if
Hartung-Knapp method was used
-
In forest plots, show correct degrees of freedom for test of effect
in subgroups for Hartung-Knapp method
-
In update.meta(), consider input for arguments 'pscale', 'irscale'
and 'irunit' for meta-analysis objects created with metagen()
User-visible changes
-
forest.meta():
- new argument 'subgroup.hetstat'
- arguments 'subgroup', 'subgroup.hetstat', 'prediction.subgroup',
'test.effect.subgroup', 'test.effect.subgroup.fixed' and
'test.effect.subgroup.random' can be a logical vector of same
length as number of subgroups
- arguments 'lab.e', 'lab.c', 'lab.e.attach.to.col' and
'lab.c.attach.to.col' renamed to 'label.e', 'label.c',
'label.e.attach' and 'label.c.attach'
-
forest.meta(), metabin(), metacont(), metacor(), metacr(),
metagen(), metainc(), metamean(), metaprop(), metarate(),
print.meta(), update.meta():
- new argument 'prediction.subgroup'
-
metamerge():
- first argument can be of class 'limitmeta' or 'copas'
-
bubble.metareg():
- new argument 'backtransf' to (not) back transform relative
treatment effects on y-axis
- new arguments 'ref', 'col.ref', 'lty.ref' and 'lwd.ref' for
reference line
-
settings.meta():
- arguments 'print', 'reset' and 'setting' can be used like any
other setting; for example, it is possible to fully reset the
settings and switch to the RevMan 5 settings
- R commands 'settings.meta("print")' and 'settings.meta()' produce
the same printout
- new global setting 'prediction.subgroup' for prediction intervals
in subgroups
- new global settings 'CIlower.blank' and 'CIupper.blank'
-
cilayout():
- new arguments 'lower.blank' and 'upper.blank' to suppress printing
of spaces in confidence intervals
- additional checks for length of arguments
Internal changes
meta 5.1-1 (2021-12-03)
Major changes
- For meta-analysis of single proportions,
- export p-value of exact binomial test for individual studies if
Clopper-Pearson method (method.ci = "CP") is used to calculate
confidence intervals for individual studies
- do not export p-value for individual studies if argument
'method.ci' is not equal to "CP" or "NAsm" (normal approximation
based on summary measure)
Bug fixes
-
Meta-analysis of continuous outcomes using Hedges' g or Cohen's d as
summary measure resulted in inestimable SMDs in individual
studies if the total
sample size was larger than 343 and argument 'exact.smd' was TRUE
(default)
-
Forest plot creation for meta-analysis of single means with
subgroups resulted in an
error
Internal changes
-
New internal function ciClopperPearson() to calculate confidence
limits and p-value for exact binomial method
-
Exported list elements changed for internal functions
ciAgrestiCoull(), ciSimpleAsymptotic() and ciWilsonScore()
meta 5.1-0 (2021-11-17)
Major changes
- By default, use exact formulae in estimation of the standardised
mean difference (Hedges' g, Cohen's d) and its standard error
(White & Thomas, 2005)
Bug fixes
- Use of metagen() with argument 'id' (three-level model) does not
result in an error if all estimates come from a single study
Internal changes
- Fix errors due to extended checks of arguments equal to NULL in R
package metafor, version 3.1 or above
meta 5.0-1 (2021-10-20)
Major changes
- For backward compatibility, use Q statistic based on Mantel-Haenszel
estimate (argument 'Q.Cochrane') by default to calculate
DerSimonian-Laird estimator of the between-study variance
Bug fixes
- For small sample sizes, use correct entry from Table 2 in Wan et.
(2014) to approximate
standard deviation from median and related statistics
meta 5.0-0 (2021-10-11)
Major changes
-
Behaviour of print.meta() and print.summary.meta() switched (to be
in line with other print and summary functions in R)
-
New default settings:
- Restricted maximum likelihood (REML) instead of DerSimonian-Laird
estimator used as default to estimate between-study heterogeneity
(argument 'method.tau')
- Do not use Q statistic based on Mantel-Haenszel estimate to
calculate DerSimonian-Laird estimator of the between-study
variance (argument 'Q.Cochrane')
- Print 'Common effect model' instead of 'Fixed effect model'
-
Default settings of meta, version 4 or lower, can be used with
command settings.meta("meta4") - this does not change the new
behaviour of print.meta() and print.summary.meta()
-
Renamed arguments:
- 'fixed' instead of 'comb.fixed'
- 'random' instead of 'comb.random'
- 'level.ma' instead of 'level.comb'
- 'subgroup' instead of 'byvar'
- 'subgroup.name' instead of 'bylab'
- 'print.subgroup.name' instead of 'print.byvar'
- 'sep.subgroup' instead of 'byseparator'
- 'nchar.subgroup' instead of 'bylab.nchar'
Internal changes
meta 4.19-2 (2021-09-30)
Bug fixes
-
Forest plots of meta-analyses assuming a common between-study
heterogeneity variance in subgroups resulted in an error
(bug was introduced in meta, version 4.16-0)
-
For GLMMs, export Wald-type Q statistic for residual heterogeneity
instead of missing value
meta 4.19-1 (2021-09-14)
Bug fixes
-
metagen():
- set random effects weights equal to zero for estimates with
standard errors equal to NA (to fix error bubble.metareg)
-
metareg():
- for three-level model, use 'test = "t"' instead of 'test = "knha"'
in internal call of rma.mv()
User-visible changes
-
summary.meta():
- print tau2 and tau for subgroups with single study if argument
'tau.common = TRUE'
-
bubble.metareg():
- show regression lines for a single categorical covariate
meta 4.19-0 (2021-08-06)
Major changes
-
Subgroup analysis for three-level model fully implemented
-
New default for forest plots to show results of test for subgroup
differences in meta-analyses with subgroups
-
Calculation of weights for three-level random effects model using
weights.rma.mv() with argument 'type = "rowsum"' from R package
metafor
-
Print study label provided by argument 'studlab' for meta-analysis
with a single study
-
Total number of observations and events printed in summaries (if
available)
Bug fixes
-
metagen():
- treatment estimates for three-level models with subgroups were not
based on common between-study variance despite argument
'tau.common = TRUE'
-
metareg():
- use rma.mv() from R package metafor for three-level models
instead of rma.uni()
User-visible changes
-
metabin(), metacont(), metacor(), metacr(), metagen(), metagen(),
metainc(), metamean(), metaprop(), metarate():
- new argument 'test.subgroup' to print results of test for subgroup
differences
-
print.meta():
- for three-level models, column with grouping information added to
study details
-
metagen():
- default for estimation of between-study variance has changed for
three-level models with subgroups, i.e., tau2 is allowed to be
different in subgroups by default
Internal changes
- metagen():
- new variable '.idx' with running index in meta-analysis dataset
(list element 'data')
- new logical list element 'three.level' indicating whether
three-level model was used
meta 4.18-2 (2021-06-11)
Bug fixes
- For argument 'adhoc.hakn = "ci"', directly compare width of
confidence intervals of Hartung-Knapp method and classic random
effects meta-analysis
meta 4.18-1 (2021-05-12)
Major changes
- Calculate correct upper limit for confidence intervals of I2 and H2
in very homogeneous meta-analyses (i.e., if Q < k - 1)
Bug fixes
-
forest.meta():
- correct order of p-values for homogeneity tests within subgroups
if argument 'bysort = TRUE'
-
calcH():
- set H = 1 in calculation of confidence interval for H if H < 1
(i.e., if Q < k - 1)
-
metabias():
- bug fix for linear regression tests using metafor, version
2.5-86
-
metabind():
- bug fix for a single meta-analysis object
Internal changes
-
metabias.bias():
- argument '...' passed on to rma.uni()
-
metagen():
- set list element 'df.hakn' to NA instead of NULL if condition met
for argument 'adhoc.hakn = "ci"'
meta 4.18-0 (2021-03-05)
Major changes
- Prediction intervals for subgroups implemented
Bug fixes
User-visible changes
Internal changes
-
metacont():
- get rid of warnings 'Unknown or uninitialised column' if argument
'subset' is used
-
subgroup():
- calculate prediction intervals for subgroups
meta 4.17-0 (2021-02-24)
Major changes
-
Tests of funnel plot asymmetry:
-
New dataset Pagliaro1992 for meta-analysis on prevention of first
bleeding in cirrhosis (Pagliaro et
al., 1992)
Bug fixes
- update.meta():
- do not switch to three-level model if method.tau = "ML"
User-visible changes
-
metabias():
- use name of first author to select test for funnel plot asymmetry
instead of "rank", "linreg", "mm", "count", and "score" (can be
abbreviated; old names are still recognised)
-
print.metabias():
- new arguments 'digits.stat', 'digits.se', 'digits.pval',
'scientific.pval', 'big.mark', 'zero.pval', 'JAMA.pval'
Internal changes
- linregcore():
- complete rewrite using rma.uni() and regtest() from R package
metafor
meta 4.16-2 (2021-01-27)
Bug fixes
- drapery():
- use correct limits on y-axis for argument 'type = "zvalue"'
User-visible changes
-
funnel.meta():
- inverse of square root of sample size can be plotted on y-axis
(argument 'yaxis = "invsqrtsize"')
-
forest.meta():
- consider input for argument 'hetstat' to print heterogeneity
statistics for overall results (see argument 'overall.hetstat')
-
metabin(), metacont(), metacor(), metagen(), metagen(), metainc(),
metamean(), metaprop(), metarate():
- studies with missing values for subgroup variable (argument
'byvar') can be excluded from meta-analysis using argument
'subset'
Internal changes
- funnel.meta():
- try to derive sample sizes from list elements 'n.e' or 'n.c' if
argument 'yaxis = "size"'
meta 4.16-1 (2021-01-19)
Bug fixes
- For argument 'adhoc.hakn = "ci"', use correct query to determine
whether confidence interval of Hartung-Knapp method is smaller than
classic random effects meta-analysis (Hybrid method 2 in Jackson et
al., 2017)
meta 4.16-0 (2021-01-18)
Major changes
-
Three-level meta-analysis models can be fitted for generic and
continuous outcomes (Van den Noortgate et.,
2013) by calling
rma.mv() from R package metafor internally
-
Measures I2 and H for residual heterogeneity are based on Q
statistic for residual heterogeneity (instead of taken directly from
metafor package)
-
Additional ad hoc method implemented if confidence interval of
Hartung-Knapp method is smaller than classic random effects
meta-analysis (Hybrid method 2 in Jackson et al.,
2017)
-
For funnel plot of a diagnostic test accuracy meta-analysis, use
effective sample size (Deeks et.,
2005) by default on
the y-axis
-
New function metamerge() to merge pooled results of two
meta-analyses into a single meta-analysis object
Bug fixes
-
metabin():
- Mantel-Haenszel method of risk differences did not use continuity
correction in case of studies with a zero cell count (argument
'MH.exact = FALSE')
-
metabin(), metainc(), metaprop(), metarate():
- for GLMMs, confidence limits for classic random effects
meta-analysis were calculated instead of confidence limits for
Hartung-Knapp if argument 'hakn = TRUE'
-
metabin(), metainc(), metaprop(), metarate():
- works for GLMMs with zero events or number of events equal to
number of patients in all studies
-
forest.meta():
- print results for test of subgroup effect in correct order if
argument 'bysort = TRUE'
-
read.rm5():
- list elements 'method' and 'sm' had been encoded as a factor
instead of character under R-versions below 4.0 which resulted in
an error using metacr()
User-visible changes
-
Do not print empty confidence intervals for heterogeneity statistics
-
metacont(), metagen(), update.meta():
- new argument 'id' to specify which estimates belong to the same
study (or laboratory) in order to use three-level model
-
metabind():
- argument '...' can be a single list of meta-analysis objects
- meta-analyses can use different methods, e.g., different
estimators of the between-study variance
-
All meta-analysis functions:
- argument 'adhoc.hakn = "iqwig6"' instead of 'adhoc.hakn = "ci"'
uses the ad hoc method for Hartung-Knapp method described in
General Methods 6.0 (IQWiG, 2020)
- argument 'adhoc.hakn = "ci"' uses the ad hoc method described in
Jackson et al. (2017)
-
forest.meta():
- column heading "Mean" instead of "MLN" for meta-analysis object
created with metamean() with arguments 'sm = "MLN"' and
'backtransf = TRUE'
- study labels specified by argument 'studlab' tried to catch from
meta-analysis object
- do not print statistic for residual heterogeneity if argument
'tau.common = FALSE' was used to conduct subgroup meta-analysis
-
metainc():
- square root transformed incidence rate difference added as new
summary measure (sm = "IRSD")
-
New arguments 'text.fixed', 'text.random', 'text.predict',
'text.w.fixed' and 'text.w,random' in meta-analysis functions
-
settings.meta():
- new general setting "geneexpr" to print scientific p-values and
not calculate confidence interval for between-study heterogeneity
variance tau2
- argument 'method.tau.ci' can be specified as a global setting
- text for fixed effect and random effects model as well as
prediction interval can be specified (arguments 'text.fixed',
'text.random', 'text.predict', 'text.w.fixed', 'text.w.randon')
-
print.meta(), print.summary.meta():
- do not print information on continuity correction for exact
Mantel-Haenszel method with single study
-
metareg() can be used in loops to provide argument 'formula'
-
New auxiliary function JAMAlabels() to create study labels in JAMA
layout
Internal changes
- Calculate measures of residual heterogeneity in hetcalc()
meta 4.15-1 (2020-10-02)
Bug fixes
- metacr():
- set summary measure to "OR" for Peto odds ratio
meta 4.15-0 (2020-09-29)
Major changes
-
Deeks' linear regression test for funnel plot asymmetry of funnel
plots of diagnostic test accuracy studies implemented (Deeks et.,
2005)
-
Effective sample size (Deeks et.,
2005) can be used
on y-axis of funnel plot
-
Discard infinite estimates and standard errors from calculation of
heterogeneity measures
-
Diagnostic odds ratio (sm = "DOR") added as new effect measure in
metabin() and metagen()
User-visible changes
-
forest.meta(), forest.metabind():
- arguments 'digits.zval' and 'print.zval' renamed to 'digits.stat'
and 'print.stat'
-
print.summary.meta(), settings.meta():
- argument 'digits.zval' renamed to 'digits.stat'
-
metacr():
- do not print a warning for inverse variance meta-analysis with
binary outcome
-
Help page for tests of funnel plot asymmetry updated
-
Help pages for metabin() and metainc() updated
meta 4.14-0 (2020-09-09)
Major changes
-
Median and related statistics can be used in meta-analysis with
continuous outcomes to approximate means and standard deviations
(Wan et., 2014; Luo
et al., 2018; Shi et
al., 2020)
-
RevMan 5 analysis datasets can be imported directly using the
RM5-file
-
R package xml2 added to Imports (RM5-files are in XML-format)
-
Confidence intervals for individual studies can be based on quantile
of t-distribution (only implemented for mean differences and raw
untransformed means at the moment)
-
For the generic inverse variance method,
- methods by Luo et
al. (2018) implemented
to estimate mean from sample size, median and other statistics
- method by Shi et al. (2020)
implemented to estimate the standard deviation from sample size,
median, interquartile range and range
Bug fixes
-
forest.meta():
- show all studies with estimable treatment effects if argument
'allstudies = FALSE'
-
metabind():
- works with meta-analysis objects created with metacor()
- calculate correct p-value for heterogeneity test if input are
subgroup analyses of the same dataset
- calculate correct p-value for within-subgroup heterogeneity test
if input are subgroup analyses of the same dataset
-
metacum():
- works with Hartung-Knapp method
-
metagen():
- list element 'seTE' contained standard deviation instead of
standard error for method by Wan
et. (2014) to estimate
mean and its standard error from median and other statistics
User-visible changes
-
read.rm5():
- direct import of RM5-file possible
- new argument 'debug' for debug messages while importing RM5-files
directly
-
metacr():
- overall results not shown if this was specified in the Cochrane
review (only applies to imported RM5-files)
-
metagen(), metacont(), metamean():
- new argument 'method.mean' to choose method to estimate mean from
sample size, median and other statistics
- new argument 'method.sd' to choose method to estimate standard
deviation from sample size, median, interquartile range and range
- new argument 'method.ci' to choose method for confidence intervals
of individual studies (only applies to mean differences and raw
untransformed means at the moment)
-
metacont():
- new arguments to estimate mean and standard deviation from median
and related statistics:
'median.e', 'q1.e', 'q3.e', 'min.e', 'max.e', 'median.c', 'q1.c',
'q3.c', 'min.c', 'max.c', 'method.mean', 'method.sd',
'approx.mean.e', 'approx.mean.c', 'approx.sd.e', 'approx.sd.c'
-
metamean():
- new arguments to estimate mean and standard deviation from median
and related statistics:
'median', 'q1', 'q3', 'min', 'max', 'method.mean', 'method.sd',
'approx.mean', 'approx.sd'
-
forest():
- by default, show number of participants in forest plot if this
information is available for meta-analysis objects created with
metagen()
- automatically format p-values for individual studies if added to
forest plot using argument 'leftcols' or 'rightcols'
-
Datasets renamed from Fleiss93, Fleiss93cont and Olkin95 to
Fleiss1993bin, Fleiss1993cont and Olkin1995
-
More sensible variable names in datasets Fleiss1993bin,
Fleiss1993cont and Olkin1995
Internal changes
-
Previous R function read.rm5() for CSV-files renamed to
read.rm5.csv()
-
New auxiliary functions extract_outcomes(), oct2txt() and
read.rm5.rm5() to import RevMan 5 analysis datasets
-
ci():
- list element 'z' renamed to 'statistic' as calculations can also
be based on the t-distribution; list element 'z' is still part of
the output for backward compatibility, however, could be removed
in a future update
-
metagen():
- list elements 'zval', 'zval.fixed' and 'zval.random' renamed to
'statistic', 'statistic.fixed' and 'statistic.random'; list
elements 'zval', 'zval.fixed' and 'zval.random' are still part of
the output for backward compatibility, however, could be removed
in a future update
-
Internal functions TE.seTE.iqr.range(), TE.seTE.iqr() and
TE.seTE.range() renamed to mean.sd.iqr.range(), mean.sd.iqr() and
mean.sd.range()
-
mean.sd.iqr.range():
- new arguments 'method.mean' and 'method.sd'
-
mean.sd.iqr(), mean.sd.range():
- new argument 'method.mean'
-
chkchar(), chkcolor(), chklevel(), chknumeric():
- argument 'single' renamed to 'length' (which can be used to test
for a specific vector length instead whether it is a single value)
(argument 'single' is still available for backward compatibility,
however, will be removed in a future update)
meta 4.13-0 (2020-07-03)
Major changes
-
Rely on generic functions from R package metafor, e.g., to
produce forest or funnel plots (since R version 4.0.0 generic
functions from an R package do not consider corresponding functions
from another R package which can result in errors if R packages
meta and metafor are both loaded)
-
R function funnel.default() removed from meta due to conflict
with metafor
meta 4.12-0 (2020-05-04)
Major changes
User-visible changes
-
drapery():
- study IDs or study labels can be printed at the top of the drapery
plot to identify individual studies
- more flexible plots, e.g., colours can be specified for individual
studies based on p-value of treatment effect
- possible value for argument 'type' renamed from "cvalue" to
"zvalue" as drapery plots show test statistics, not critical
values
-
funnel.meta(), funnel.default():
- argument 'log' is considered for relative summary measures, e.g.,
odds or risk ratio
-
metaprop():
- can be used with non-integer number of events and sample sizes
-
metabias.meta(), metabias.default():
- third component of list element 'estimate' renamed from "slope" to
"intercept" for linear regression tests
-
settings.meta():
- new possible general settings: "iqwig5" and "iqwig6", respectively
-
Use Markdown for NEWS
meta 4.11-0 (2020-02-20)
Major changes
-
New arguments 'overall' and 'overall.hetstat' in meta-analysis
functions to control printing of overall meta-analysis results
(useful to only show subgroup results)
-
For GLMMs, use Wald-type Q statistic to calculate I2 of residual
heterogeneity in meta-analysis with subgroups (instead of
likelihood-ratio Q statistic)
Bug fixes
User-visible changes
-
forest.meta():
- possible to print results for test of an overall effect or
subgroup differences even if meta-analysis results are not shown
- new defaults for arguments 'overall' and 'overall.hetstat' (which
are now considered from meta-analysis objects)
-
print.summary.meta():
- for meta-analysis with subgroups, print information on Q and I^2
with fixed effect results and information on tau and tau^2 with
random effects results (previously, information on Q, I^2, tau,
and tau^2 was reported twice)
Internal changes
- do not calculate confidence limits for tau2 and tau in intermediate
calculations of other quantities (i.e., use argument 'method.tau.ci
= ""')
meta 4.10-0 (2020-01-29)
Major changes
- New function drapery() to generate a drapery plot which is based on
p-value curves
Bug fixes
- funnel.meta():
- print contours in contour-enhanced funnel plots at correct
position for relative effect measures (bug was introduced in
meta, version 4.9-8)
User-visible changes
-
update.meta():
- do not print a warning concerning argument 'Q.Cochrane' if
argument 'sm = "ASD"' for meta-analysis objects created with
metabin()
-
print.summary.meta():
- do not print z- and p-values if test for an overall effect was not
conducted; see argument 'null.effect' in metamean(), metaprop(),
and metarate()
meta 4.9-9 (2019-12-19)
Bug fixes
- forest.meta():
- printing an additional column on the right side of the forest plot
does not result in an error (bug was introduced in meta,
version 4.9-8)
User-visible changes
-
labbe():
- new argument 'pos.studlab'
- argument checks implemented
-
baujat(), bubble():
- argument 'pos' renamed to 'pos.studlab'
- argument checks implemented
meta 4.9-8 (2019-12-16)
Major changes
-
Confidence intervals for the between-study variance tau2 and its
square root tau are calculated
-
Print tau as well as confidence intervals for tau2 and tau in
outputs
-
Square root of between-study variance can be printed in forest plots
instead of between-study variance tau2; in addition, the confidence
interval for tau2 or tau can be printed
-
Use R package metafor to estimate between-study variance tau2
for DerSimonian-Laird and Paule-Mandel method (which has been
already used for all other methods to estimate tau2)
-
For Mantel-Haenszel (MH) method, report results as MH method
(instead of inverse variance, IV) for meta-analysis of binary
outcome with a single study (results are identical for MH and IV
method in this situation)
-
Number of studies printed without digits in forest plots for R
objects created with metabind()
-
P-values can be printed according to JAMA reporting standards
-
In subgroup analyses, print the group labels instead of levels if
the grouping variable is a factor
-
In funnel plot, print funnel around random effects (instead of fixed
effect) estimate if only random effects meta-analysis is conducted;
only show funnel if either fixed effect or random effects
meta-analysis was conducted
-
New preferred citation of R package meta: Balduzzi et
al. (2019)
User-visible changes
-
print.summary.meta(), forest.meta():
- new argument 'JAMA.pval' to print p-values according to JAMA
reporting standards
-
print.summary.meta():
- new argument 'zero.pval' to remove leading zeros from p-values
- print information on estimation of between-study variance even if
only results for fixed effect model is shown
- print information if Mantel-Haenszel estimate is used to calculate
Q and tau2 (implemented similar to RevMan 5)
- global setting for 'text.tau2' as defined in settings.meta() is
considered in details of meta-analytical method
-
print.meta():
- do not print (missing) weights for GLMMs
-
update.meta():
- by default, do not print warnings (argument 'warn')
- add information on variable defining subgroups (argument 'byvar')
to meta-analysis dataset
-
Command 'settings.meta("JAMA")' will change the settings for
arguments 'zero.pval' and 'JAMA.pval'
-
Help page with description of R package updated
-
Major update of other help pages:
- metacont(), metacor(), and metamean()
Internal changes
-
Function paulemandel() removed as R package metafor is used to
estimate the between-study variance
-
formatPT():
-
List elements 'C' and 'C.w' (scaling factor to estimate common
between-study variance) removed from meta-analysis objects
-
Import confint.rma.uni() from metafor to calculate confidence
intervals for tau2 and tau
-
New internal function pasteCI() to print formatted CIs
-
New internal function is.wholenumber() to check for whole numbers
meta 4.9-7 (2019-09-28)
Major changes
- Subgroup analysis using argument 'byvar' possible for generalised
linear mixed models (GLMMs)
Bug fixes
User-visible changes
- Major update of help pages:
- metabin(), metagen(), metainc(), metaprop(), metarate()
meta 4.9-6 (2019-08-06)
Major changes
-
New functions to calculate the number needed to treat from the
results of a meta-analysis
-
Equivalence limits can be added to forest plots
-
Font family can be specified in forest plots
-
Print Wald-type test of heterogeneity for generalised linear mixed
models (problem fixed in R package metafor, version 2.1-0)
Bug fixes
-
forest.meta():
- (always) print correct length for reference line
- (always) print label on x-axis at the correct vertical position
- (always) print graph labels on the left and right side of the
forest plot at the correct vertical position
- no error if additional numeric variable is added to the right side
of the forest plot (argument 'rightcols')
-
summary.meta():
- consider argument 'bylab'
-
metaprop():
- allow values 0 and 1 for argument 'null.effect'
User-visible changes
-
forest.meta():
- new arguments 'lower.equi', 'upper.equi', 'lty.equi', 'col.e' and
'fill.equi' to add equivalence limits
- new argument 'fontfamily' to specify the font family
-
forest.metabind():
- information on heterogeneity printed for each meta-analysis
Internal changes
meta 4.9-5 (2019-04-11)
Major changes
-
For the generic inverse variance method, treatment estimates and
standard errors of individual studies can be derived from
- p-value or confidence limits
- sample size, median, interquartile range and / or range (Wan et
al. (2014), BMC Med Res Meth, 14, 135)
-
New functions for the conversion of effect measures:
- smd2or() - from standardised mean difference to log odds ratio
- or2smd() - from log odds ratio to standardised mean difference
-
Harbord test for funnel plot asymmetry implemented for risk ratio as
effect measure
-
Generalised linear mixed model is the new default method for
meta-analysis of single proportions using the logit transformation
-
R packages metafor and lme4 moved from Suggests to Imports
-
Suppress printing of Wald-type test of heterogeneity for generalised
linear mixed models (problem in R function rma.glmm() from R package
metafor, version 2.0-0)
-
Use roxygen2 for development of R package meta
User-visible changes
Bug fixes
-
metacum(), metainf():
- consider argument 'method' for meta-analysis objects created with
metaprop() or metarate()
-
forest.meta():
- argument 'studlab' can be used with objects created with metacum()
or metainf()
-
subgroup():
- return subgroup sample sizes for objects created with metagen()
Internal changes
-
New internal functions TE.seTE.ci(), TE.seTE.iqr(),
TE.seTE.iqr.range(), TE.seTE.range(), and seTE.ci.pval() to
approximate treatment estimates or standard errors from other
information
-
setchar():
- new argument 'stop.at.error'
-
metagen():
- list element 'data' contains the dataset of the meta-analysis
object (i.e., list element 'data') instead of the whole
meta-analysis object
meta 4.9-4 (2019-01-03)
Major changes
- Information on residual heterogeneity in meta-analyses with
subgroups shown in printouts and forest plots
User-visible changes
- forest.meta():
- new arguments 'resid.hetstat' and 'resid.hetlab' to control
printing of information on residual heterogeneity in meta-analyses
with subgroups
Bug fixes
- forest.meta():
- works in meta-analyses with subgroups if argument 'allstudies =
FALSE'
meta 4.9-3 (2018-11-29)
Major changes
- New argument 'control' in meta-analysis functions which is passed on
to R function rma.uni() or rma.glmm() from R package metafor to
control the iterative process to estimate the between-study variance
tau^2
User-visible changes
-
metabin(), metacont(), metacor(), metagen(), metainc(), metamean(),
metaprop(), metarate(), update.meta():
- new argument 'control' (see major changes)
-
forest.meta():
- new argument 'calcwidth.subgroup'
Bug fixes
- bubble.metareg():
- ignore missing values in covariate to calculate limits on x-axis
- works if dataset used to create meta-analysis object is a tibble
instead of a data frame
Internal changes
meta 4.9-2 (2018-06-07)
Major changes
- All p-values of Q statistics are list elements of meta-analysis
objects
Bug fixes
- metareg():
- consider argument 'intercept = FALSE' if argument 'formula' has
been provided
Internal changes
- New internal function replaceNULL()
meta 4.9-1 (2018-03-22)
Major changes
-
Subgroup results consider the exclusion of individual studies (bug
fix)
-
For generalised linear mixed models, between-study variance set to
NA if only a single study is considered in meta-analysis
Bug fixes
-
metamean():
- use of argument 'byvar' for subgroup analyses possible
-
metacor(), metamean(), metaprop(), metarate():
- use as input to metabind() possible
-
Internal function subgroup():
- consider argument 'exclude' in subgroup analyses
-
Internal function bylevs():
- drop unused levels if subgroup variable is a factor variable
User-visible changes
Internal changes
meta 4.9-0 (2017-12-05)
Major changes
-
New function metamean() to conduct meta-analysis of single means
-
New function metabind() to combine meta-analysis objects, e.g. to
generate a forest plot with results of several subgroup analyses
-
Subgroup analysis implemented for generalised linear mixed models
(GLMMs) with and without assumption of common between-study variance
(arguments 'byvar' and 'tau.common')
-
Axis direction can be reversed for x-axis in forest plots
-
Source code version of meta can be installed without
compilation, i.e., without use of Rtools on Windows or 'Command-line
tools for Xcode' on macOS
-
Rank test for funnel plot asymmetry uses cor() from R package
stats instead of internal C routine (negligibly slower, however,
no need for compilation of source installs)
-
Thousands separator can be used in printouts and forest plots for
large numbers
-
P-values equal to 0 are actually printed as "0" instead of "<
0.0001"
User-visible changes
-
forest.meta(), print.meta(), print.summary.meta():
- new argument 'big.mark' to specify character printed as thousands
separator, e.g., big.mark = "," will result in printing of "1,000"
instead of "1000"
-
forest.meta():
- sensible forest plot generated if first value in argument 'xlim'
is larger than second value, e.g. xlim = c(10, -10)
- separator between label and levels of grouping variable (argument
'byseparator') is considered from meta-analysis object
- for relative summary measures, e.g., odds ratio and risk ratio,
labels on x-axis are not rounded to two digits (which resulted in
the value 0 for a tick-mark at 0.001)
- bug fix: lines for treatment effect in fixed effect and random
effects model start in center of diamond if argument 'hetstat =
FALSE'
- bug fix: argument 'type.study' will be sorted according to
arguments 'sortvar'
-
metaprop():
- arguments 'byvar' and 'tau.common' can be used for GLMMs
-
Help page with overview of R functions in R package meta updated
Internal changes
-
New internal functions:
- is.log.effect() to check for treatment effects combined on log
scale
- is.mean() to check whether summary measure refers to meta-analysis
of single means
-
Renamed internal functions:
- formatCI() instead of p.ci()
- formatN() instead of format.NA()
- formatPT() instead of format.p()
-
Removed R functions:
- format.tau() as functionality is now provided by formatPT()
- C program kenscore.c as cor() from R package stats is used
instead to calculate Kendall's tau
-
Deprecated functions: format.NA(), format.p(), p.ci()
-
Check whether argument 'sm' is NULL in meta-analysis functions
-
subgroup(): extended for GLMMs
-
formatPT():
- zero p-values are printed as "0" instead of "< 0.001"
- NaNs are handled like NAs
-
bylabel(), catmeth(), formatPT(), formatN(), xlab():
- new argument 'big.mark' (see above)
meta 4.8-4 (2017-08-11)
User-visible changes
- forest.meta():
- new arguments 'col.fixed' and 'col.random' to change colour of
fixed effect and random effects lines
Bug fixes
-
bubble.metareg():
- works if covariate in metareg() is not part of dataset used to
generate meta-analysis object
-
forest.meta():
- lines for treatment effect in fixed effect and random effects
model always start in center of diamond
-
metacum(), metainf():
- argument 'model.glmm' considered for metabin() and metainc()
objects
-
print.summary.meta():
- print transformed null effect for meta-analysis of single
correlations, proportions, or rates if argument 'backtransf =
FALSE', i.e., for metacor(), metaprop(), and metarate() objects
-
trimfill.meta():
- argument 'null.effect' is considered to calculate p-value for
fixed effect and random effects model for metacor(), metaprop(),
and metarate() objects
Internal changes
-
New internal functions is.cor(), is.prop() and is.rate() to check
whether summary measure refers to meta-analysis of correlations,
proportions, or rates
-
metabias.default(), radial.default(), trimfill.default():
- call metagen() internally to create meta-analysis object
- call metabias.meta(), radial.meta(), or trimfill.meta() internally
to conduct analysis
meta 4.8-3 (2017-07-22)
Major changes
-
Similar to RevMan 5, individual studies can be excluded from
meta-analysis, however, will be shown in printouts and forest plots
-
In forest plots, line spacing can be determined by the user
User-visible changes
-
metabin(), metacor(), metacont(), metagen(), metainc(), metaprop(),
metarate():
- new argument 'exclude' to exclude studies from meta-analysis
-
forest.meta():
- new argument 'spacing' to determine line spacing
- bug fix for for meta-analysis with standardized mean difference
(sm = "SMD") and argument 'layout = "RevMan5"'
-
R function ci() can be used with vectors or matrices of treatment
estimates and standard errors and a single value for argument 'df',
i.e., degrees of freedom (which is used in R package netmeta to
calculate prediction intervals for network meta-analysis estimates)
-
metacum(), metainf():
- argument 'null.effect' considered internally for objects generated
with metacor(), metagen(), metaprop() and metarate()
Internal changes
- baujat.meta(), metabias.meta(), metacum(), metainf(), forest.meta(),
funnel.meta(), metareg(), print.meta(), radial.meta(),
trimfill.meta(), update.meta():
- changes to deal with excluded studies
meta 4.8-2 (2017-05-24)
Major changes
-
Calculate confidence interval for I2 in a meta-analysis with two
studies if the heterogeneity statistic Q is larger than 2
-
P-values can be printed in scientific notation
-
In forest plots, printing of z-values can be disabled and labels for
tests can be changed by user
User-visible changes
-
forest.meta():
- new argument 'print.zval' to print (default) or not print z-value
for test of treatment effect
- new argument 'print.Q.subgroup' to print (default) or not print
Chi-squared statistic for test of subgroup differences
- bug fix: print first line above second line if argument 'xlab'
consists of two lines (bug was introduced in meta, version
4.8-0)
- labels of additional columns are printed in correct line if label
consists of two lines
- new argument 'scientific.pval' to print p-values in scientific
notation, e.g., 1.2345e-01 instead of 0.12345
- arguments 'label.test.overall.fixed', 'label.test.overall.random',
'label.test.subgroup.fixed', 'label.test.subgroup.random',
'label.test.effect.subgroup.fixed',
'label.test.effect.subgroup.random' work as expected
- new argument 'text.subgroup.nohet' to enable the user to change
the text "not applicable" in the line with heterogeneity
statistics for a subgroup with less than two studies contributing
to the meta-analysis
- forest plot without any study contributing to meta-analysis can be
generated without an error, e.g., meta-analysis with binary
outcome, sm="OR", and all event numbers equal to zero
-
print.meta() and print.summary.meta():
- new argument 'scientific.pval' to print p-values in scientific
notation, e.g., "1.2345e-01" instead of "0.12345"
- new arguments 'print.pval' and 'print.pval.Q' to specify number of
significant digits for p-values
-
R command 'help(meta)' can be used to show brief overview of R
package meta
-
Substantially decrease number of automatically run examples for
forest.meta() as CRAN only allows a run time below 10 seconds for
examples provided on a help page
Internal changes
meta 4.8-1 (2017-03-17)
User-visible changes
- metacum(), metainf():
- bug fix for meta-analysis objects without continuity correction,
i.e., metacont(), metacor(), metagen() (bug was introduced in
meta, version 4.8-0)
- bug fix for metarate() objects due to improper use of metaprop()
internally
meta 4.8-0 (2017-03-12)
Major changes
- Continuity correction can be specified for each individual study in
meta-analysis with proportions or incidence rates
User-visible changes
Internal changes
-
act on NOTE in CRAN checks with R version, 3.4.0, to register and
declare native C routine 'kenscore'
-
metabin(), metainc():
- new list element 'k.MH' with number of studies in meta-analysis
using Mantel-Haenszel method
-
forest.meta():
- auxiliary R functions removed from R code
- cleaning / shortening of R code
-
new auxiliary R functions used in forest.meta():
- add.label(), add.text(), add.xlab(), draw.axis(),
draw.ci.square(), draw.ci.diamond(), draw.ci.predict(),
draw.forest(), draw.lines(), formatcol(), removeNULL(), tg(),
tgl(), twolines(), wcalc()
-
hetcalc(), calcH():
- set heterogeneity statistics tau2, H and I2 to NA if only a single
study contributes to meta-analysis
-
updateversion():
- use R function update.meta() if version of meta used to create
R object is below 3.2
meta 4.7-1 (2017-02-13)
Major changes
-
Null hypothesis for test of an overall effect can be specified for
metacor(), metagen(), metaprop(), and metarate(); for all other
meta-analysis functions implicit a null effect of zero is assumed
(for relative effect measures, e.g., odds ratio and hazard ratio,
the null effect is defined on the log scale)
-
User can choose whether to print the following heterogeneity
quantities: I^2, H, Rb (by default, heterogeneity measure Rb is not
printed and thus revoking a change in meta, 4.7-0)
-
In forest plots with subgroups, study weights are summed up to 100
percent within each subgroup if no overall estimates are requested,
i.e., argument 'overall = FALSE' (like before, by default, weights
are not printed if argument 'overall = FALSE' and have to be
explicitely requested using argument 'leftcols' or 'rightcols')
User-visible changes
-
forest.meta():
- print line with heterogeneity statistics directly below individual
study results if pooled effects are not shown in forest plot
(overall = FALSE)
- print right and left labels (arguments 'label.left',
'label.right') in correct line if arguments 'overall = FALSE' and
'addrow = FALSE'
- bug fix: do not stop with an error if 'comb.fixed = FALSE',
'comb.random = FALSE', and 'overall.hetstat = TRUE'
-
ci(), metacor(), metagen(), metaprop(), metarate():
- new argument 'null.effect' to specify null hypothesis for test of
an overall effect, e.g., null.effect = 0.5 in metaprop() to test
whether the overall proportion is equal to 0.5
-
metagen():
- Hartung-Knapp method only used for at least two studies in
meta-analysis
-
print.meta():
- print covariate with subgroup information for each study, if
subgroup analysis is conducted (argument 'byvar')
-
print.summary.meta():
- new arguments 'print.I2', 'print.H' and 'print.Rb' to specify
heterogeneity measures shown in output
- new arguments 'text.tau2', 'text.I2' and 'text.Rb' to change text
printed to identify respective heterogeneity measure
- only print information on double zero studies if argument
'allstudies = TRUE'
- print results for (empty) subgroup in meta-analysis with two
studies and one subgroup with missing treatment estimate
-
settings.meta():
- new arguments 'print.I2', 'print.H', 'print.Rb', 'text.tau2',
'text.I2' and 'text.Rb' to modify printing of heterogeneity
measures
Internal changes
- summary.meta():
- bug fix renaming list element 'ircale' renamed to 'irscale'
- list element 'within' removed which has not been used since
meta, version 1.1-4
meta 4.7-0 (2016-12-16)
Major changes
-
Forest plots:
- forest plots with RevMan 5 and JAMA layout
- use of mathematical symbols for I^2, tau^2, etc.
- individual study results can be omitted from forest plot
(especially useful to only print subgroup results)
- labels can be printed at top of forest plot
-
Measure of between-study heterogeneity added:
-
Default settings of meta-analysis methods specified via gs() instead
of extracting elements of list .settings (which makes output of
args() easier to read, e.g., args(metabin))
-
Version of suggested R package metafor must be at least 1.9-9
(due to change in arguments of rma.uni() and rma.glmm())
User-visible changes
-
forest.meta():
- argument 'layout':
- new layout "JAMA" to produce forest plots according to the
*JAMA Network, Instructions for Authors"
- RevMan 5 layout extended
- arguments can be specified without using grid::unit():
'plotwidth', 'colgap', 'colgap.left', 'colgap.right',
'colgap.studlab', 'colgap.forest', 'colgap.forest.left',
'colgap.forest.right'
- new argument 'study.results' to print (default) or omit individual
study results from forest plot
- new argument 'bottom.lr' to change position of labels on left and
right side of forest plot
- new arguments 'col.label.right' and 'col.label.left' to change
colour of labels on left and right side of forest plot
- argument 'weight' renamed to 'weight.study' and new argument
'weight.subgroup' added to specify whether plotted subgroup
results should be of same or different size
- new arguments 'print.Rb', 'print.Rb.ci' and 'Rb.text' for
heterogeneity measure Rb
- new arguments to control printing: 'digits.cor', 'digits.mean',
'digits.sd', 'digits.time', 'digits.zval'
- new argument 'print.subgroup.labels' to print (default) or omit
rows with subgroup label from forest plot
- new argument 'type.subgroup' to change plotting of subgroup
results
- argument 'addspace' renamed to 'addrow'
- new argument 'addrow.subgroups' to add a blank line between
subgroup results
- new argument 'addrow.overall' to add a blank before meta-analysis
results
- new argument 'blanks' to enhance printing of test statistics,
heterogeneity measures, and p-values
- new argument 'colgap.studlab' to specify space between column with
study labels and subsequent column
- new arguments to change width of column with study labels (these
arguments are especially useful if only study labels are printed
on left side of forest plot):
- 'calcwidth.fixed' (consider text for fixed effect model)
- 'calcwidth.random' (consider text for random effects model)
- 'calcwidth.hetstat' (consider text for heterogeneity measures)
- 'calcwidth.tests' (consider text for tests of effect or
subgroup differences)
- new column "effect.ci" with estimated treatment effect and
confidence interval in one column
- unnecessary arguments removed: 'text.I2', 'text.tau2'
-
metabin(), metacont(), metacor(), metacr(), metacum(), metagen(),
metainc(), metainf(), metaprop(), metarate(), trimfill.default(),
trimfill.meta():
- new measure of between-study heterogeneity implemented (list
elements 'Rb', 'lower.Rb', 'upper.Rb')
-
summary.meta():
- new measure of between-study heterogeneity added (list element
'Rb.w')
-
print.meta(), print.summary.meta():
- print heterogeneity measure Rb
-
metabias.meta(), metabias.default():
- checks for arguments implemented
-
New function gs() to get default settings
-
forest.meta(), metabin(), metacont(), metacor(), metacr(),
metagen(), metainc(), metaprop(), metarate(), print.meta(),
print.summary.meta():
- use gs() to define defaults for arguments in meta-analysis
functions, e.g. gs("hakn") instead of .settings$hakn
-
metareg():
- stop with an error if version of metafor package is below
1.9-9
-
metabin(), metainc(), metaprop(), metarate():
- for GLMMs, stop with an error if version of metafor package is
below 1.9-9
-
metabin():
- bug fix, do not stop with an error if no double zero events are
present in a dataset with at least one study with NA event counts
-
metareg():
- bug fix, use of covariate 'x' does not result in an error
-
settings.meta():
- general settings for RevMan 5 and JAMA implemented
- function can be used to change the layout of confidence intervals
using arguments 'CIbracket' and 'CIseparator' which can also be
set using cilayout()
-
Several help pages updated, especially
- forest.meta(), settings.meta(), meta-package
Internal changes
-
metabin(), metainc(), metaprop(), metarate(), metareg():
- use argument 'test' instead of 'knha' and 'tdist' for calls of
rma.uni() and rma.glmm(); change in R package metafor, version
1.9-9
-
subgroup():
- new measure Rb of between-study heterogeneity implemented
-
is.installed.package():
- new check of version number of R package
- use requireNamespace() instead of installed.packages()
-
format.p():
- for small p-values, print "p < 0.01" or "p < 0.001" instead of "p
< 0.0001" if digits.pval is 2 or 3, respectively
- new argument 'zero' to print ".001" instead of "0.001", etc
-
meta-internal():
- set defaults for arguments 'smrate' and 'layout'
meta 4.6-0 (2016-10-13)
Major changes
-
New function metarate() to conduct meta-analysis of single incidence
rates
-
Peters' test for funnel plot asymmetry implemented for
meta-analysis of single proportions
-
Meta-analysis of ratio of means added to metacont()
-
Justification of additional columns in forest plot can be
specified individually for each additional column
-
Justification of additional columns in forest plot can be
specified individually for each additional column
-
Calculation of Freeman-Tukey double arcsine transformation and
back transformation slightly changed in meta-analysis of single
proportions
-
By default, do not print a warning if back transformation for
metaprop() and metarate() objects results in values below 0 or
above 1 (only for proportions); note, respective values are set
to 0 or 1
User-visible changes
-
Help page with brief overview of meta package added
-
Preferred citation of meta package in publications changed; see
output of command 'citation("meta")'
-
forest.meta(), metagen(), print.meta(), print.summary.meta(),
summary.meta(), trimfill.default(), trimfill.meta(), update.meta():
- new arguments 'irscale' and 'irunit' for meta-analysis objects
created with metarate()
-
settings.meta():
- new arguments 'smrate' for meta-analysis objects created with
metarate()
-
funnel.meta(), funnel.default():
- new argument 'pos.studlab' to change position of study labels
-
forest.meta():
- new arguments 'just.addcols.left' and 'just.addcols.right' to
specify justification of additional columns on left and right side
of forest plot
-
metacont():
- meta-analysis for ratio of means implemented (argument 'sm =
"ROM"')
- new argument 'backtransf' for ratio of means (argument 'sm =
"ROM"')
-
metaprop():
- change in Freeman-Tukey double arcsine transformation only visible
in printouts if argument 'backtransf = FALSE' or if list elements
'TE', 'TE.fixed', and 'TE.random' (as well as confidence
intervals) are extracted from a metaprop object
-
print.summary.meta():
- bug fix in subgroup() to print correct results for subgroup
analyses of metaprop objects with argument 'sm = "PFT"'
-
print.meta(), print.summary.meta():
- new argument 'warn.backtransf' to specify whether a warning should
be printed if backtransformed proportions and rates are below 0
and back transformed proportions are above 1
-
Help pages updated:
- forest.meta(), metabias.meta(), metabin(), metacont(), metacor(),
metagen(), metainc(), metainf(), metaprop(), print.meta(),
print.summary.meta(), summary.meta(), trimfill.default(),
trimfill.meta(), update.meta()
Internal changes
-
New function asin2ir() to back transform arcsine transformed
incidence rates
-
backtransf(), catmeth(), metacum(), metainf(), subgroup(), xlab():
- extension to handle meta-analysis objects created with metarate()
-
metaprop(), asin2p():
- calculation of Freeman-Tukey double arcsine transformation changed
to get similar estimates as arcsine transformation, i.e. multiply
values by 0.5
-
subgroup():
- bux fix in calculation of harmonic mean of sample sizes for
metaprop() objects with argument 'sm = "PFT"' and event times for
metarate() objects with argument 'sm = "IRFT"'
meta 4.5-0 (2016-08-17)
Major changes
-
New features in forest plots:
- printing of columns on left side of forest plot can be omitted
- total person time can be printed
- text for fixed effect and random effects model can be omitted from
calculation of width for study labels
- plot type for confidence intervals (square or diamond) can be
specified for each study as well as fixed effect and random
effects estimate
- printing of test for treatment effect in subgroups possible
-
New function weights.meta() to calculate absolute and percentage
weights in meta-analysis
-
New argument 'byseparator' to define the separator between label and
subgroup levels which is printed in meta-analysis summaries and
forest plots - considered in all R functions dealing with
meta-analysis and subgroups
-
Argument 'pscale' - a scaling factor for printing of single event
probabilities - considered in all R functions for single
proportions; before this update, argument 'pscale' was only
available in forest.meta()
User-visible changes
-
forest.meta():
- argument 'ref' considered for metaprop() objects
- argument 'leftcols = FALSE' omits printing of columns on left side
of forest plot
- new argument 'pooled.times' to print total person time
- new argument 'calcwidth.pooled' to include or exclude text from
pooled estimates to determine width of study labels
- new argument names (old names can still be used at the moment,
however, will result in an informative warning message):
- 'col.i' -> 'col.study'
- 'col.i.inside.square' -> 'col.inside'
- 'col.diamond.fixed.lines' -> 'col.diamond.lines.fixed'
- 'col.diamond.random.lines' -> 'col.diamond.lines.random'
- new arguments:
- 'type.study', 'type.fixed', 'type.random' to use squares or
diamonds to plot treatment effects and confidence intervals
- 'col.inside.fixed', 'col.inside.random' with information on
colour to print confidence interval inside square
- 'test.effect.subgroup', 'test.effect.subgroup.fixed',
'test.effect.subgroup.random',
'label.test.effect.subgroup.fixed',
'label.test.effect.subgroup.random', 'fs.test.effect.subgroup',
'ff.test.effect.subgroup' to print results for test of treatment
effect in subgroups
- bug fix to get correct length for reference line and lines for
fixed effect and random effects estimate if argument 'test.overall
= TRUE'
- bug fix to consider arguments 'lab.e.attach.to.col' and
'lab.c.attach.to.col' for metagen() objects
-
metabin(), metacont(), metacor(), metagen(), metainc(), metaprop(),
forest.meta(), print.summary.meta(), summary.meta(), update.meta(),
settings.meta():
- new argument 'byseparator'
-
metagen(), metaprop(), print.meta(), print.summary.meta(),
summary.meta(), trimfill.meta(), trimfill.default(), update.meta():
-
labbe.metabin(), labbe.default():
- transformed event probabilites can be plotted, e.g., log odds
event probabilities for odds ratio as summary measure
- line for null effect added by default; see arguments 'nulleffect',
'lwd.nulleffect', 'col.nulleffect'
-
metabin(), metainc(), metaprop():
- use predict.rma() from metafor package to calculate prediction
interval for GLMM method
- print note for GLMM method that continuity correction is only used
to calculate individual study results
-
Help pages updated:
- labbe.metabin(), labbe.default(), forest.meta(), metabin(),
metacont(), metacor(), metagen(), metainc(), metaprop(),
print.meta(), print.summary.meta(), summary.meta(),
trimfill.meta(), trimfill.default(), update.meta()
Internal changes
meta 4.4-1 (2016-06-20)
User-visible changes
- metareg(), update.meta():
- bug fix for error if used with metaprop() object and argument
'method = "GLMM"'
meta 4.4-0 (2016-05-14)
Major changes
-
Generalised linear mixed models (GLMMs) implemented by internal call
of rma.glmm() from R package metafor by Wolfgang Viechtbauer
-
R packages lme4, numDeriv, and BiasedUrn added to
suggested packages which are required by rma.glmm()
-
Print layout (especially number of printed digits) slightly modified
which impacts output from print.meta(), print.summary.meta(), and
forest.meta()
-
New arguments to change number of digits in printouts and forest
plots
User-visible changes
-
metabin(), metainc(), metaprop():
- extension for meta-analysis based on GLMM; see argument 'method'
and 'model.glmm' (not used in metaprop())
- new argument '...' to provide additional arguments to rma.glmm()
- some arguments can be used for other meta-analysis methods than
inverse variance method: 'method.tau', 'hakn', 'tau.common',
'TE.tau, 'tau.preset'
-
metabin():
- do not print warning that inverse variance instead of
Mantel-Haenszel method is used for analysis of a single study
- print warning if continuity correction (arguments 'incr',
'allincr', 'addincr', 'allstudies') is used with arcsine
difference, Peto method, or GLMM
- check whether R package BiasedUrn is installed for conditional
hypergeometric-normal GLMM (method = "GLMM", model.glmm = "CM.EL")
-
forest.meta():
- extension to plot meta-analysis based on GLMM
- argument 'labels' can be used instead of argument 'label' to
change labels on x-axis
-
funnel.meta():
- print default labels on y-axis with capital first letter
-
metareg() and update.meta():
- extension for meta-analysis based on GLMM
-
print.meta():
- new arguments to control printing: 'digits.se', 'digits.zval',
'digits.Q', 'digits.tau2', 'digits.H', 'digits.I2', 'digits.prop',
'digits.weight'
- argument '...' passed on to internal call of print.summary.meta()
-
print.summary.meta():
- new arguments to control printing: 'digits.zval', 'digits.Q',
'digits.tau2', 'digits.H', 'digits.I2'
- print "--" for missing z-value instead of "NA"
- only print confidence interval for H and I2 if lower and upper
limits are not NA
- print Wald-type and Likelihood-Ratio heterogeneity test for GLMMs
-
settings.meta():
- new arguments: 'model.glmm', 'digits', 'digits.se', 'digits.zval',
'digits.Q', 'digits.tau2', 'digits.H', 'digits.I2', 'digits.prop',
'digits.weight', 'digits.pval', 'digits.pval.Q'
- check whether R package metafor is installed for specific
values of argument 'method.tau'
- check whether R packages required for GLMMs are available (if
method = "GLMM"): metafor, lme4, numDeriv
-
Help pages updated:
metabin(), metainc(), metaprop(), metareg(), forest(),
print.meta(), print.summary.meta(), settings.meta(), update.meta()
Internal changes
-
New function format.NA() to print other text than "NA" for missing
values
-
metagen():
- only call paulemandel() if heterogeneity statistic Q is larger
equal than number of studies minus 1
(otherwise between-study heterogeneity tau2 is set equal to 0)
-
metabin(), metainc(), metaprop(), summary.meta():
- new list elements 'model.glmm', '.glmm.fixed', '.glmm.random',
'version.metafor'
-
metabin(), summary.meta():
- new list element 'doublezeros' for odds ratio or risk
ratio as summary measure
-
Set defaults for arguments 'model.glmm', 'digits', 'digits.se',
'digits.zval', 'digits.Q', 'digits.tau2', 'digits.H', 'digits.I2',
'digits.prop', 'digits.weight', 'digits.pval', 'and digits.pval.Q'
-
paulemandel():
- more sensible warning if maximum number of iterations is reached
- maximum number of iterations increased from 25 to 100
-
format.p():
-
catmeth():
- print information for GLMMs
- print information whether studies with double zeros are included
in meta-analysis
-
is.installed.package():
- new arguments for more flexible error and warning messages:
'func', 'argument', 'value', 'chksettings'
meta 4.3-2 (2015-12-02)
-
metacont():
- bug fix to calculate correct treatment estimates for individual
studies for Glass's delta
-
metaprop():
- print correct error message if number of events is larger than
number of observations
meta 4.3-1 (2015-11-16)
-
forest.meta():
- new arguments 'digits.se', 'digits.tau2', 'digits.pval',
'digits.pval.Q', 'digits.Q', 'digits.I2' to control printing of
standard errors, p-values, tau2 and heterogeneity statistics
- new arguments 'test.overall' and 'test.subgroup' controlling
whether information on test for overall effect and heterogeneity
should be printed
-
Internal function paulemandel():
- bug fix to give studies with missing treatment effect and standard
error zero weight in random effects meta-analysis
- do not stop estimation algorithm if estimated tau2 is negative
-
settings.meta():
- bug fix for error if used with an unassigned argument
-
format.p(), format.tau():
- new argument 'digits' to round p-values and tau2 values
-
chkchar(), chkclass(), chklength(), chklevel(), chklogical(),
chkmiss(), chknull(), chknumeric(), setchar():
- new argument 'name' to change name of checked argument in printout
-
Help page of forest.meta() updated
meta 4.3-0 (2015-07-02)
-
metabin(), metainc(), and metaprop():
- allow missing values in numbers of events or patients
(corresponding studies get zero weight in meta-analysis)
-
forest.meta():
- print information on test for overall effect (arguments
'test.overall.fixed' and 'test.overall.random')
- print information on test for subgroup differences in
meta-analysis with subgroups (arguments 'test.subgroup.fixed' and
'test.subgroup.random')
- new argument 'layout' to change layout of forest plot
- argument 'lab.NA' considered for all columns in forest plot, e.g.,
numbers of events and patients for metabin()
- new argument 'lab.NA.effect' to label NAs in individual treatment
estimates and confidence intervals
- bug fix for error if random effects estimate is missing
-
metareg():
- additional arguments implemented ('hakn', 'level.comb',
'intercept')
- argument '...' is no longer ignored but passed on to rma.uni(),
e.g., to control the iterative estimation process
- bug fix to conduct fixed effect meta-regression (argument
'method.tau = "FE"')
-
metabin():
- use inverse variance instead of Mantel-Haenszel method if only a
single study has a non-missing treatment estimate or standard
error
-
settings.meta():
- code added for new arguments in forest.meta() to print information
on tests
-
Help pages of metareg() and forest.meta() and link to RevMan webpage
updated
meta 4.2-0 (2015-05-08)
-
Copyright changed (new names for Institute and Medical Center)
-
metacont():
- new argument 'exact.smd' to implement exact formulae for Hedges' g
and Cohen's d (White and Thomas (2005; Hedges, 1981)
- use formula from Borenstein et al. (2009) to calculate standard
error for Cohen's d
-
forest.meta():
- bug fix to appropriately sort additional columns provided in
arguments 'leftcols' and 'rightcols' if argument 'sortvar' is not
missing
- new argument 'print.I2.ci' to print confidence intervals for I2
-
forest.meta(), print.meta, print.summary.meta():
- prediction interval can be printed if random effects estimate is
not shown
-
settings.meta(), catmeth(), update.meta():
- code added for new argument 'exact.smd' in metacont()
-
ci(), kentau():
- calculate p-values without floating point number representation
problems, e.g., the command ci(9, 1) does not result in a p-value
of 0 but 2.257177e-19
-
Several help pages updated to reflect changes in metacont() and
RevMan 5 reference
meta 4.1-0 (2015-02-04)
meta 4.0-3 (2015-01-07)
- metabin():
- bug fix for error in printing of results for Mantel-Haenszel or
Peto method if any study has zero events in both groups
meta 4.0-2 (2014-12-06)
-
metabin():
- bug fix for error if Peto method is used
- argument 'sm = "ASD"' for arcsine difference instead of 'sm =
"AS"' (abbreviations 'sm = "AS"' and 'sm = "A"' can still be used)
-
metabin(), metacont(), metacor(), metagen(), metainc(), and
metaprop():
- weights 'w.random.w' are calculated from random effects
meta-analysis ignoring subgroup membership; internal function
subgroup() changed accordingly
- argument 'tau.common = TRUE' if argument 'tau.preset' is not NULL
in subgroup analyses
meta 4.0-1 (2014-11-19)
- forest.meta():
- bug fix for meta-analyses with subgroups if additional columns
were provided in argument 'leftcols' or 'rightcols'
meta 4.0-0
Major revision
This update has been declared as major revision as R code to conduct
subgroup analyses has been moved from summary.meta() and forest.meta()
to metabin(), metacont(), metacor(), metagen(), metainc(), and
metaprop(). Accordingly, an R object generated with these functions
contains all results from subgroup analyses.
In the case of subgroups, the overall treatment effect in fixed effect
and random effects meta-analysis ignores subgroup membership. See
Borenstein et al. (2011), Introduction to Meta-Analysis, Wiley,
Chapter 19, "Obtaining an overall effect in the presence of subgroups,
Option 3.
Furthermore, several checks of function arguments have been
implemented in version 4.0-0 of meta.
Details
-
Function addvar() removed from R package meta as functionality
is provided by forest.meta()
-
forest.meta():
- new meaning for argument 'just' which determines the justification
of all columns but study labels (argument 'just.studlab') and
columns added to the forest plot (argument 'just.addcols')
- new argument 'just.addcols' to change justification of text in
additional columns
- new arguments 'text.I2' and 'text.tau2'
- for metaprop objects, values "n" and "event" handled as standard
columns in argument 'rightcols' and 'leftcols', i.e. justification
is determined by argument 'just.cols'
- subgroup results printed with the same polygon height as overall
results, i.e. percentage weight is not considered to determine
polygon height for subgroups
-
bubble.metareg():
- bug fix for meta-regression without intercept
- bug fix for error in meta-regression using specific effect
measure, e.g. 'sm = "RR"', "OR", or "HR"
-
New internal R functions:
- subgroup(), hetcalc()
- updateversion()
- bylevs(), byvarname()
- chkchar(), chkclass(), chklength(), chklevel(), chklogical(),
chkmetafor() chkmiss(), chknull(), chknumeric()
- int2num(), npn()
- setchar(), setstudlab()
-
format.p(), format.tau(), catmeth(), print.summary.meta():
- consider settings for option 'OutDec' (character used as decimal
point in output conversions), e.g., options(OutDec = ",") will
print "1,0" instead of "1.0"
-
print.meta(), print.summary.meta():
- print 'p-value' instead of 'p.value'
-
print.summary.meta():
- remove code for R objects created with version 2.0-0 or lower of
meta
-
Several help pages updated
meta 3.8-0 (2014-09-12)
-
forest.meta(), funnel.default(), funnel.meta(), metabin(), metacor,
metacr(), metagen(), metainc(), metaprop(), print.meta(),
print.summary.meta, summary.meta(), trimfill.default(),
trimfill.meta():
- new argument 'backtransf' indicating whether effect measures
should be back transformed
-
print.meta(), print.summary.meta():
- argument 'logscale' replaced by 'backtransf'
-
print.summary.meta(), forest.meta():
- print prediction interval for Freeman-Tukey double arcsine
transformation (sm = "PFT")
-
forest.meta():
- consider prediction interval to calculate limits on x-axis if
argument 'prediction = TRUE'
-
bubble.metareg():
- new argument 'regline' indicating whether regression line should
be added to plot
-
settings.meta():
- new argument 'print' to print listing of all settings as function
call without arguments does not print settings any longer
- list with previous settings can be provided as sole input
-
New functions:
- backtransf() to control back transformation of effect measures
- is.relative.effect() to check for relative effect measures
-
File DESCRIPTION:
- R package grid defined as Imports instead of Depends
-
Help pages updated to reflect changes in version 3.8-0
meta 3.7-1 (2014-07-29)
meta 3.7-0 (2014-07-11)
-
metaprop():
- new argument 'method.ci' to implement various methods to calculate
confidence intervals for individual studies (default:
Clopper-Pearson method which is also called 'exact' binomial
method)
- list elements 'zval.fixed', 'pval.fixed', 'zval.random' and
'pval.random' set to NA
-
New internal functions:
- ciWilsonScore() used in metaprop()
- ciAgrestiCoull() used in metaprop()
- ciSimpleAsymptotic() used in metaprop()
- estimate.missing() used in trimfill.meta() and trimfill.default()
-
metacont():
- new argument 'pooledvar' to conduct meta-analysis of mean
differences based on pooled variance for individual studies
-
update.meta():
- function can be used to upgrade R objects created with older
versions of meta, i.e. all versions between 0.5 and 3.6-0
- extended to objects of the following classes:
- trimfill()
- metacum()
- metainf()
- new arguments:
- 'method.ci' for metaprop() objects
- 'pooledvar' for metacont() objects
- 'left', 'ma.fixed', 'type' and 'n.iter.max' for trimfill()
objects
- new list element 'call.object' with call used to generate
meta-analysis object
-
as.data.frame.meta(), baujat.meta(), forest.meta(), funnel.meta(),
labbe.metabin(), metacum(), metainf(), print.meta(), summary.meta,
trimfill.meta():
- call update.meta() to update meta-analysis objects created with
meta, version < 3.7
-
metabin(), metacont(), metacor(), metagen(), metainc(), metaprop(),
trimfill.default(), trimfill.meta():
- new list elements 'lower', 'upper', 'zval' and 'pval' with
confidence limits, z- and p-values for individual studies
-
print.meta(), print.summary.meta():
- print information on method used for confidence intervals of
individual studies
-
metacum(), metainf():
- add code for metainc() objects
- new list element 'call' with function call
- consider argument 'pooledvar' for metacont() objects
-
metabin(), metacont(), metacor(), metagen(), metainc(), metaprop():
- study labels will only be converted to characters for factor
variables
-
Help pages
- updated to reflect changes in version 3.7-0
- argument 'tau.preset' correctly described as the square-root of
the between-study variance
meta 3.6.0
meta 3.5-1 (2014-05-14)
-
metabin():
- inverse variance method used instead of Mantel-Haenszel method if
argument 'tau.common = TRUE'
-
metareg():
- tilde sign not necessary in argument 'formula' to make this
function more user friendly
-
forest.meta():
- print common tau2 for subgroups if argument 'tau.common = TRUE' in
meta-analysis object
-
metagen():
- arguments 'n.e' and 'n.c' can be part of the dataset provided in
argument 'data'
- DerSimonian-Laird method used instead of Paule-Mandel method if
argument 'tau.common = TRUE'
-
metacor(), metainc(), and metaprop():
- store value of arguments 'title', 'complab', and 'outclab' in
meta-analysis object
-
Some help pages (slightly) updated
meta 3.5-0 (2014-04-19)
-
New R function settings.meta() to define and print default settings
for meta-analyses in R package meta
-
metagen():
- Hartung and Knapp method added; previously rma.uni() from R
package metafor was called for this method
- Paule-Mandel method to estimate between-study variance implemented
using new internal function paulemandel() which is based on
mpaule.default() from R package metRology by S.L.R. Ellison
<s.ellison at lgc.co.uk> (Author of mpaule.default() is S. Cowen
<simon.cowen at lgc.co.uk> with amendments by S.L.R. Ellison)
-
metacont():
- studies with missing treatment estimate get zero weight in
meta-analysis
-
metabin(), metacont(), metacor(), metacr(), metagen(), metainc(),
metaprop():
- default values changed according to settings.meta()
-
metareg():
- use argument 'method.tau = "REML"' if this argument is equal to
"PM" for meta-analysis object
-
Several help pages updated
meta 3.2-1 (2014-03-26)
- forest.meta():
- bug fix to show correct confidence limits for individual studies
if argument 'level' is not equal to the default 0.95. (bug was
introduced in meta, version 3.0-0)
meta 3.2-0 (2014-03-12)
-
metabin(), metacont(), metacor(), metagen(), metainc(), metaprop():
- heterogeneity statistics I2 and H added to R object
- column names changed in list element 'data'; columns starting with
a "." used internally in update.meta()
- string "byvar" is used as default label for grouping
variable if argument 'bylab' is not provided
-
metareg():
- variable '.byvar' used instead of 'byvar' to reflect change in
list element 'data'
-
update.meta():
- arguments 'byvar' and 'subset' fully functional
- variables '.TE', ... used internally instead of TE, ... to reflect
change in list element 'data'
-
trimfill.default(), trimfill.meta():
- heterogeneity statistics I2 and H added to R object
-
metagen():
- bug fix to correctly calculate weights (list elements 'w.fixed'
and 'w.random') if any standard error is missing or zero for the
Hartung-Knapp method (argument 'hakn = TRUE') or the DerSimonian
Laird method is not used (argument 'method.tau' not equal to "DL")
-
summary.meta():
- subgroup analysis implemented for metainc() objects
-
forest.meta():
- groups will not be sorted automatically in alphabetical order (new
argument 'bysort'). Use argument 'bysort = FALSE' to get the old
behaviour of forest.meta()
-
forest.meta(), summary.meta():
- only (re)calculate heterogeneity statistics (Q, tau2, I2) for R
objects generated with older versions of R package meta
-
catmeth():
- new argument 'tau.preset' to print information if between-study
variance was pre-specified
-
print.meta(), print.summary.meta():
- argument 'tau.preset' used in catmeth()
-
New internally used functions isquared() and calcH()
-
Some help pages updated
meta 3.1-2 (2013-12-01)
- forest.meta():
- bug fix for error in meta-analyses with subgroups using any but
metaprop() (bug was introduced in meta, version 3.1-1)
meta 3.1-1 (2013-11-20)
- forest.meta():
- bug fix to show random effects estimate in metaprop() objects with
subgroups using argument 'sm = "PFT"'
meta 3.1-0 (2013-11-12)
-
New R function metainc() for meta-analysis of incidence rates
-
Continuity correction:
- metabin() and metaprop() do no longer print a warning in case of
studies with a zero cell frequency
- instead information on continuity correction is given under
"Details on meta-analytical method" if a corresponding
meta-analysis object is printed
-
forest.meta(), funnel.default(), funnel.meta(), print.meta(),
print.summary.meta(), update.meta(), catmeth(), xlab():
- properly handle R objects of class "metainc"
-
metaprop():
- use correct variable names for 'event' and 'n' in list element
'data' if metaprop() is called without argument 'data'
-
metabin():
- inverse variance method (argument 'sm = "Inverse"') is used
automatically if argument 'tau.common = TRUE'
- bug fix for error if argument 'tau.common = TRUE' and 'method =
"MH"'
-
catmeth():
- print information on continuity correction for objects of class
"metabin", "metaprop", and "metainc"
-
summary.meta():
- fixed effect and random effects estimates and confidence intervals
are only (re)calculated for R objects created with meta,
version < 2 if argument 'level.comb' has not been used
-
trimfill.meta(), trimfill.default():
- new list elements 'lower.fixed', 'upper.fixed', 'zval.fixed',
'pval.fixed', 'lower.random', 'upper.random', 'zval.random',
'pval.random' added to trimfill() object (bug was introduced in
meta, version 2.0-0)
-
New datasets smoking and lungcancer as examples for metainc()
meta 3.0-1 (2013-09-18)
Major revision
This update has been declared as major revision as the user interface
changed by dropping some arguments:
- print.meta(), forest.meta(), summary.meta(): 'level',
'level.prediction'
- print.meta(), forest.meta(), metainf(), metacum(): 'level.comb'
- in forest.meta(), summary.meta(): 'byvar'
This functionality is now provided by update.meta().
Details
-
New function update.meta() to update an existing meta-analysis
object created with metabin(), metacont(), metagen(), metaprop(), or
metacor()
-
New function cilayout() to change layout of confidence intervals
-
Deprecated function plot.meta() removed
-
metabin(), metacont(), metagen(), metaprop(), metacor():
- code cleaning for new R function update.meta()
-
metabin(), metacont(), metagen(), metaprop(), metacor(),
summary.meta():
- new list components:
- 'data' with original data used in function call
- 'subset' with information on subset used in meta-analysis
-
metareg():
- argument 'data' renamed to 'x'
- first two arguments interchanged (which is now in line with other
R functions from R package meta)
- information on grouping variable (list element 'byvar') is
utilised if argument 'formula' is missing
- any column from original dataset (list element 'data') can be
used in meta-regression
-
trimfill.meta():
- new defaults for arguments 'comb.fixed' and 'comb.random' (by
default only random effects estimate calculated)
- arguments 'sm' and 'studlab' removed
- new list elements (depending on class of meta-analysis object
used in function call):
- 'event.e', 'event.c', 'event' with number of events
- 'n.e', 'n.c', 'n' with number of observations
- 'mean.e', 'mean.c', 'sd.e', 'sd.c' with means and standard
deviations
- 'cor' with correlation
- 'class.x' with class of meta-analysis object used in function
call
-
trimfill.default():
- only calculate random effects estimate by default
-
metacr():
- new list elements 'event.e', 'n.e', 'event.c' and 'n.c' for Peto
O-E method
-
metaprop():
- new list element 'incr.event'
-
forest.meta():
- bug fix for error if (i) the effect measure is equal to RR, OR, or
HR and (ii) argument 'label' is not a logical value
-
print.summary.meta():
- print "0" instead of "< 0.0001" if between-study heterogeneity is
zero
-
New function format.tau() to print "0" instead of "< 0.0001" if tau2
is zero
-
p.ci():
- new arguments 'bracket.left', 'separator' and 'bracket.right' for
more flexible confidence interval layouts
-
Several help pages updated
meta 2.5-1 (2013-08-09)
-
forest.meta():
- new argument 'just.studlab' to change justification of study
labels
-
print.meta():
- print correct information on method to calculate approximate
confidence interval for metaprop() with a single study
-
trimfill.meta():
- new list elements 'title', 'complab', 'outclab', 'label.e',
'label.c', 'label.left' and 'label.right'
meta 2.5-0 (2013-07-25)
-
metacr():
- new arguments 'prediction' and 'level.predict' for prediction
interval for a new study
- new argument 'tau.common' for common tau2 across subgroups
- new arguments 'level' and 'level.comb' for confidence interval of
single studies or meta-analysis
-
trimfill.meta(), trimfill.default():
- new arguments 'prediction' and 'level.predict'
-
forest.meta():
- heterogeneity statistics are only shown if results for fixed
effect or random effects model are plotted
-
metagen(), metabin(), metacont(), metaprop(), metacor():
- list elements 'comb.fixed', 'comb.random', and 'prediction' are
set to FALSE for a single study
-
print.meta(), print.summary.meta():
- new argument 'logscale' to print results for summary measures
"RR", "OR", "HR", or "PLN" on logarithmic scale
-
Several help pages updated
meta 2.4-1 (2013-06-20)
-
metaprop():
- bug fix for error in forest.meta() (bug was introduced in
meta, version 2.4-0)
- new list elements 'incr', 'allincr' and 'addincr' added (bug was
introduced in meta, version 1.5-0)
-
print.meta():
- new arguments 'prediction' and 'level.predict' to print prediction
interval for a new study
-
forest.meta(), print.summary.meta():
- only print warnings in internal call of asin2p() if result for
fixed effect, random effects model or prediction interval are
printed
-
asin2p():
- new argument 'warn' to only print warnings for meta-analysis results
-
Example to generate forest plot added to help pages of metabin(),
metacont(), metacor(), metacr(), metagen(), metaprop()
meta 2.4-0 (2013-06-17)
-
metagen(), metabin(), metacont(), metaprop(), metacor():
- new arguments 'prediction' and 'level.predict' (prediction
interval for a new study)
- new argument 'tau.common' (common tau2 across subgroups)
- help pages updated accordingly
-
metaprop():
- new default summary measure (sm = "PLOGIT")
- deprecated argument 'freeman.tukey' removed
-
summary.meta():
- new arguments 'prediction' and 'level.predict'
- list element 'tau.common' from meta-analysis object considered
- correct values for list elements 'incr', 'allincr', and 'addincr'
used in calculations for metaprop() objects
-
forest.meta():
- new arguments for prediction interval: 'prediction',
'level.predict', 'text.predict', 'col.predict',
'col.predict.lines', 'fs.predict', 'fs.predict.labels',
'ff.predict', 'ff.predict.labels"
- correct values for list elements 'incr', 'allincr', and 'addincr'
used in calculations for metaprop() objects
- information on confidence limit printed for pooled estimates if CI
level is different from CI level for individual studies
-
print.summary.meta():
- new argument 'prediction'
- new list element 'tau.common'
-
catmeth():
- print information on use of common tau2 across subgroups
meta 2.3-0 (2013-05-12)
-
forest.meta():
- results for fixed effect and random effects models only
(re)calculated for meta-analysis objects created with meta,
version < 2
-
metabin():
- bug fix for error if argument 'sm = "RR"' and 'allstudies = TRUE'
in meta-analysis with zero events in both groups
meta 2.2-1 (2013-03-21)
meta 2.2-0 (2013-03-12)
-
metabin():
- studies with all events in both groups will be included in
meta-analysis by default (in older meta versions these studies
were only included if argument 'allstudies = TRUE')
- standard error is positive for studies with all events in both
groups (see Hartung & Knapp (2001), Stat Med, equation (18))
-
forest.meta():
- values provided by argument 'xlim' will be used as x-axis label
for relative effect measures like risk ratio or odds ratio
- default values for arguments 'smlab.pos' and 'xlab.pos' changed to
always fall within plotting range
meta 2.1-4 (2012-11-29)
meta 2.1-3 (2012-11-20)
- forest.meta():
- bug fix for metacum() or metainf() object with Freeman-Tukey
double arcsine transformation (error message: 'Error in if
(col$range[1] <= TE.fixed & TE.fixed <= col$range[2]) ...')
meta 2.1-2 (2012-10-25)
meta 2.1-1 (2012-08-12)
-
summary.meta():
- list element 'k0' added to trim-and-fill object
-
print.summary.meta():
- print number of added studies for trim-and-fill method
meta 2.1-0 (2012-05-18)
-
trimfill.meta(), trimfill.default():
- new arguments 'hakn' and 'method.tau'
-
metacum(), metainf():
- add class "trimfill" for trim-and-fill objects
-
catmeth(), print.meta(), print.summary.meta():
- print information on trim-and-fill method
-
metabias.meta(), funnel.meta():
- print error message if used with metacum() or metainf() object
-
funnel.meta():
- use different plot symbols (argument 'pch') for trimfill() object
-
.onLoad():
- version nummer of meta is printed when library is loaded
-
Help pages:
- arguments 'hakn' and 'method.tau' documented in trimfill.meta()
and trimfill.default()
- changed default for argument 'pch' in funnel.meta() documented
meta 2.0-4 (2012-05-03)
meta 2.0-2 (2012-04-17)
- metaprop():
- warning is printed if any sample size is smaller than 10 for
Freeman-Tukey double arcsine transformation
meta 2.0-1 (2012-04-04)
- metabin(), metacont(), metacor(), metagen(), metaprop():
- arguments 'subset' and 'byvar' can be of different length
meta 2.0-0 (2012-03-20)
Major revision
R package meta linked to R package metafor to provide
additional statistical methods, e.g. meta-regression and other
estimates for tau2 (REML, ...)
Details
-
New functions:
- metareg() meta-regression
- metabias() generic method for metabias()
- metabias.default() generic method for metabias()
- metabias.meta() generic method for metabias()
- metabias.rm5() generic method for metabias()
- print.rm5() generic method for rm5-object
- print.summary.rm5() generic method for rm5-object
- summary.rm5() generic method for rm5-object
- catmeth() internal function
- crtitle() internal function
- hypergeometric() internal function
- is.installed.metafor() internal function
- kentau() internal function
- linregcore() internal function
- p2logit() internal function
-
metabin(), metacont(), metagen():
- new arguments 'label.left' and 'label.right' to add label on left
or right side of forest plot
-
metabin(), metacont(), metacor(), metagen(), metaprop():
- new arguments:
- 'hakn' (Hartung-Knapp method)
- 'method.tau' (estimation method for tau2)
- 'tau.preset' (fixed value for tau)
- 'TE.tau' (pre-specified treatment effect to estimate tau)
- 'method.bias' (test for funnel plot asymmetry used in metabias)
- 'warn' (print warning messages)
- new list elements in meta-analysis object:
- 'se.tau2' with standard error of tau2
- 'hakn' for Hartung-Knapp method
- 'method.tau' with information on estimation method for tau2
- 'tau.preset' for fixed tau value
- 'TE.tau' for pre-specified treatment effect to estimate tau
- 'method.bias' for test of funnel plot asymmetry used in
metabias()
- argument 'warn = FALSE' suppresses additional warning messages
-
metabin():
- studies are excluded from meta-analysis if (event.e > n.e |
event.c > n.c) or (n.e <= 0 | n.c <= 0) or (event.e < 0 | event.c
< 0)
-
metacum(), metainf():
- return NULL if function is used with a single study
- arguments 'hakn', 'method.tau', 'tau.preset', 'method.bias',
'label.left', 'label.right' are considered from meta-analysis
object
- argument 'level' removed
-
metaprop():
- correct variance 1 / (n + 0.5) instead of 1 / (n + 1) is used for
the Freeman-Tukey double arcsine transformation (argument 'sm =
"PFT"')
-
asin2p():
- completely rewritten as back transformation of Freeman-Tukey
transformed proportions was inaccurate
- back transformation of Freeman-Tukey proportions according to
Miller (1978) - see help page of metaprop()
-
print.metabias():
- print a warning if number of studies is too small to conduct a
test for funnel plot asymmetry
-
print.summary.meta():
- new argument 'bylab.nchar'
- print test for subgroup differences for both fixed effect and
random effects model
- invisible(NULL) returned for metacum() and metainf() objects
-
metacr():
- new arguments:
- 'sm' (summary measure)
- 'method' (pooling method)
- 'comb.fixed' (fixed effect model)
- 'comb.random' (random effects model)
- 'swap.events' (only for binary data)
- 'method.tau' (estimation method for between-study variance)
- 'hakn' (Hartung-Knapp adjustment)
- 'title' (Title of Cochrane review)
- 'complab' (Comparison label)
- 'outclab' (Outcome label)
- 'warn' (print warning messages)
- removed argument:
- 'smother' (summary measure)
- return NULL if no data is available for selection of arguments
'comp.no' and 'outcome.no'
-
read.rm5():
- changed substantially for reading of RevMan 5.1 files
-
summary.meta():
- arguments 'hakn', 'method.tau', 'tau.preset', 'method.bias' are
considered from meta-analysis object
- argument 'warn = FALSE' suppresses additional warning messages
-
forest.meta():
- treatment effect and 95% confidence interval is printed in the
correct order for objects of class "metaprop" if argument 'sort'
or 'order' is used
- symmetric forest plot by default (argument xlim = "s")
- new arguments:
- 'smlab', 'smlab.pos', 'fs.smlab', 'fflab' for label of summary
measure at top of figure
- 'label.right', 'label.left', 'fs.lr', 'ff.lr' for label on right
and left side below the x-axis
- 'overall.hetstat' to show heterogeneity information for overall
effect
-
funnel.default(), funnel.meta():
- arguments 'col.fixed' and 'col.random' are recognised
-
metabias.default(), metabias.meta():
- new argument 'k.min' to only conduct test for funnel plot
asymmetry if number of studies in meta-analysis is larger or equal
to 'k.min'
- new argument '...' (ignored at the moment)
-
trimfill.default(), trimfill.meta():
- return 'invisible(NULL)' if number of studies is smaller than 3
-
New datasets: amlodipine, cisapride
-
File FLEISS93.MTV moved from directory data to directory extdata
-
Several help pages updated
-
Some new help pages added
meta 1.6-1 (2010-10-28)
meta 1.6-0 (2010-06-21)
meta 1.5-0 (2010-05-06)
-
Version jump to 1.5-0 as several changes have been implemented
-
New functions:
- metacor() meta-analysis of correlations
- forest() generic method for forest plots
- forest.meta() generic method for forest plots
- radial() generic method for radial plots
- radial.default() generic method for radial plots
- radial.meta() generic method for radial plots
- asin2p() internal function
- logit2p() internal function
- xlab() internal function
- z2cor() internal function
-
forest.meta():
- new arguments 'pooled.totals' and 'pooled.events' to specify
whether total number of observations and events should be
displayed in the plot
- new argument 'pscale' to rescale proportions for objects of class
"metaprop"
- arguments 'label' and 'xlim' are recognised for other effect
measures than RR, OR, and HR
- arguments 'rightlabs' and 'leftlabs' accept NAs for columns using
default labels
- significant digits are printed uniformly
- correct sum of percentage weight is printed for random effects
model in forest plots with subgroups
- x limits (min,max) of the plot are defined by the width of
confidence intervals instead of (0,1) for objects of class "metaprop"
-
metaprop():
- implementation of additional transformations: log transformation,
logit transformation, raw, i.e. untransformed, proportions
- new argument 'sm' to choose summary measure (i.e. transformation)
- use of argument 'freeman.tukey' is deprecated (replaced by
argument 'sm')
-
funnel(), funnel.meta(), labbe(), labbe.meta():
-
trimfill(), trimfill.meta():
-
summary.meta():
- new list elements 'H.w', 'I2.w', 'Q.b.fixed' and 'Q.b.random' for
heterogeneity statistics within subgroups
-
forest.meta(), metacum(), metainf(), print.meta(),
print.summary.meta(), summary.meta():
- extension for meta-analysis of correlations
-
plot.meta():
- print warning that function was replaced by forest.meta()
-
New list element 'version' with information on version number of
meta package used to create an object; applies only to object
creating functions, e.g. metabin() and metabias()
-
Several help pages updated
-
Use file NEWS instead of ChangeLog to document changes
meta 1.1-8 (2010-01-12)
- summary.meta(), print.summary.meta():
- test for subgroup differences is not calculated and printed for
meta-analyses using the Mantel-Haenszel method for binary data
meta 1.1-7 (2010-01-11)
- metabin(), metacont(), metagen(), metaprop():
- sensible default value is used for argument 'bylab' if argument
'byvar' is not missing
meta 1.1-6
- forest():
- additional columns are printed in the correct order if argument
'sort' or 'order' is used
meta 1.1-5 (2009-12-21)
- forest():
- new argument 'digits' specifying minimal number of significant
digits for treatment estimate and its confidence interval
meta 1.1-4 (2009-11-04)
meta 1.1-3 (2009-10-30)
- Generic method for trim-and-fill method: trimfill(),
trimfill.default(), trimfill.meta()
meta 1.1-2 (2009-10-11)
-
L'Abbe plot implemented: labbe(), labbe.default(), labbe.metabin()
-
Generic method for funnel plots: funnel(), funnel.default(),
funnel.meta()
-
funnel.meta(), funnel.default():
- contour-enhanced funnel plots can be produced (new arguments
'contour.levels', 'col.contour', 'ref')
- study labels can be printed on funnel plot (new arguments
'studlab', 'cex.studlab')
- line type, width and colour can be changed for fixed effect
treatment effect (new arguments 'lty.fixed', 'lwd.fixed',
'col.fixed')
- random effects treatment effect can be plotted (new arguments
'comb.random', 'lty.random', 'lwd.random', 'col.random')
- new default values for some arguments:
- 'pch = 21' (previously: 'pch = 1')
- 'comb.fixed = x$comb.fixed'
- background colour of points in funnel plot can be changed (new
argument 'bg')
-
forest():
- new default values for arguments 'lab.e' and 'lab.c':
- x$label.e and x$label.c (if these values are NULL the old
default values "Experimental" and "Control" are used)
-
metabin(), metacont(), metagen():
- arguments 'label.e' and 'label.c' added
-
metacr():
- use arguments 'label.e' and 'label.c' in calls to metabin(),
metacont(), metagen()
meta 1.0-6 (2009-08-31)