NEWS
meta 9.0-0
Major changes
-
The exact Mantel-Haenszel method is the new default for common effect
meta-analysis with a binary outcome; argument MH.exact in metabin() is now
TRUE. Thus, continuity corrections are no longer added to cell frequencies
when calculating Mantel-Haenszel pooled estimates for studies with zero cells.
For a single-study meta-analysis with a zero cell, a continuity correction
is still used. Use settings.meta("meta8") to restore the previous behaviour.
-
Defaults for forest plots have been revised. In the default layout
(layout = "meta"), all default study-level columns are now printed on
the left side of the forest plot. Details of the meta-analysis methods,
tests for an overall effect, and a header line are printed by default.
The previous default layout remains available via
settings.meta("meta8") or forest(..., layout = "meta8").
Furthermore, the arguments leftcols and rightcols are now honored for
all layouts, allowing users to customize the columns on either side of the
forest plot. Columns specified in rightcols are removed from the left
side if they would otherwise be printed on both sides.
Forest-plot formatting arguments can now also be supplied as named lists,
including fs, ff, col, calcwidth, print, label, colgap, just,
digits, test, type, fill, pooled, text, lty, and lwd. The
corresponding individual list.element arguments remain supported.
-
metagen() now always stores null.effect on the transformed analysis
scale. If argument transf = FALSE, the supplied value is transformed
before being stored.
-
Function asin2ir() renamed to ft2ir() to reflect that it is the inverse
of the Freeman-Tukey transformation of incidence rates.
-
Forest plots can now include a customisable main title, using the
meta-analysis title by default.
-
Cluster-robust variance estimators are now available for univariate random
effects meta-analysis and three-level models.
(Tipton and Pustejovsky, 2015;
Pustejovsky and Tipton, 2022).
-
Cumulative meta-analysis and leave-one-out analyses now return random effects
results when prediction intervals are requested and both common effect and
random effects analyses are available.
-
R package meta now requires R (>= 4.1.0).
User-visible changes
-
metabin(), metacont(), metacor(), metagen(), metainc(),
metamean(), metaprop(), metarate(), metareg(), update.meta():
- argument
method.random.ci can be equal to "CR0", "CR1", or "CR2" for
cluster-robust variance estimators
- argument
title is used as default for argument main in forest.meta()
-
forest.meta():
- column spacing has been improved for
layout = "meta8"
- for all layouts but
layout = "RevMan5", information on tests for an
overall effect are printed before heterogeneity statistics
- new arguments
main, just.main, xpos.main, gap.main, fs.main,
ff.main, col.main, and lineheight.main can be used to add and format
a main title
- arguments
smlab, xlab, label.left, and label.right can contain
more than two lines
- visible labels for pooled estimates, heterogeneity statistics, tests,
subgroup results, additional lines, and details are considered when
calculating horizontal spacing; new defaults for arguments:
calcwidth.predict, calcwidth.hetstat, calcwidth.tests,
calcwidth.subgroup, calcwidth.addline, and calcwidth.details are
TRUE
- argument
calcwidth.pooled prevents pooled labels from overlapping columns
containing pooled-row information by reserving additional space
- consider the width of treatment group labels (arguments
label.e and
label.c in meta-analysis functions) attached to columns when calculating
column widths, and suppress these labels if the attached column already has
a two-line heading
- the default font size for x-axis tick labels matches the font size of
heterogeneity statistics, details, statistical tests, additional lines, and
risk of bias legends
- less vertical space is added below overall results in JAMA layout
- allow different colours for multiple overall common effect and
random effects diamonds, prediction intervals, and their outlines
- new argument
col.study.text to specify colours for text in individual
study rows; excluded studies are printed in lightgrey by default
- allow different colours for subgroup diamonds and prediction intervals
compared with overall results; new arguments
col.diamond.common.subgroup,
col.diamond.random.subgroup, col.diamond.lines.common.subgroup,
col.diamond.lines.random.subgroup, col.predict.subgroup, and
col.predict.lines.subgroup
- arguments
random.subgroup and prediction.subgroup can be logical
matrices to select subgroup random effects estimates or prediction intervals
separately for each available confidence- or prediction-interval method,
e.g., random.subgroup = df.random.w > 1
- center combined treatment-group headers over both columns in BMJ layout for
meta-analyses of binary outcomes, continuous outcomes, or incidence rates
- left-align the risk-of-bias table header
- new argument
just.rob to specify the justification of the risk-of-bias
table heading; the heading now spans all risk-of-bias columns
- print labels for pooled estimates and heterogeneity statistics or details on
the left side if study labels are printed on the right side, and suppress
these labels if argument
leftcols is FALSE
- the reporting base for event frequencies is printed in the forest plot using
the JAMA layout for the meta-analysis of single proportions or rates
(issue #104)
- print number of events per number of observations or person-time below
x-axis (argument
xlab) instead of above the forest plot (argument smlab)
(related to issue #106)
- deprecated arguments
*.fixed and *.fixed.* have been removed. Use
the corresponding elements *.common and *.common.* of the
fs, ff, col, and label lists instead.
-
forest.metacum():
- new arguments
layout and main to select the forest plot layout and
specify its title
- new arguments to control printing of heterogeneity statistics, their
confidence intervals, and CID probabilities:
print.I2, print.I2.ci, print.tau2, print.tau2.ci,
print.tau, print.tau.ci, print.Q, print.pval.Q, and print.cidprop
- use default colours for squares regardless of layout
(issue #96)
- print the title "Cumulative Meta-Analysis"
-
forest.metainf():
- print the title "Leave-One-Out Meta-Analysis"
-
metagen():
- study-level confidence limits supplied in arguments
lower and upper
are now retained only if arguments level and level.ci agree
(issue #99)
- if they differ, confidence limits are recalculated using a normal
approximation and a warning identifies the affected studies
(issue #99)
- print a warning if supplied values for
TE, lower, and upper
suggest that the treatment estimate is not approximately halfway between
the confidence limits
(issue #99)
- correctly transform proportions supplied in arguments
TE, lower, and
upper for Freeman-Tukey double arcsine transformed proportions
(sm = "PFT") if argument transf = FALSE; sample sizes must be supplied
in argument n.e
- stop with an error if argument
n.c is provided for meta-analysis of
single proportions, incidence rates, means, or correlations
- check argument
null.effect on the original scale for meta-analyses of
single proportions, incidence rates, means, or correlations if argument
transf = FALSE
(issue #103)
-
metacor(), metamean(), metarate():
- use summary-measure specific checks for argument
null.effect
(issue #103)
-
New setting log.prefix allows users to define the prefix for
log-transformed effect measures. The default prefix is now "log" instead
of "ln" in printouts and forest plots.
-
print.meta():
- print the type of meta-analysis in the details of the meta-analysis
- always print the null hypothesis if argument
null.effect is not NA
-
metabias():
- report the response variable used in meta-regression for linear regression
tests
- radial plot can be created for Deeks' test (arguments
method = "Deeks"
and plotit = TRUE)
(pull #92)
-
drapery(), funnel.meta():
- draw plots on the analysis scale but show back-transformed tick marks
for transformed proportions, incidence rates, means, or correlations if
argument
backtransf = TRUE
(issue #102)
- for these transformed summary measures, user-supplied x-limits in argument
xlim are interpreted on the original scale if argument backtransf = TRUE
- new argument
at can be used in funnel.meta() to specify tick marks on
the x-axis
- new argument
axes can be used in drapery() to suppress axes and the plot
box
-
bubble(), funnel.meta():
- use the null effect stored in the meta-analysis object as default for the
reference line in meta-analyses of single proportions, incidence rates,
means, or correlations
(issue #102)
-
metaadd():
- function no longer available for Freeman-Tukey transformed
proportions (
sm = "PFT") or rates (sm = "IRFT")
-
Functions that ignore additional arguments in argument ... now print a
warning if such arguments are supplied.
-
New function ir2ft() to calculate the Freeman-Tukey transformation of
incidence rates. If argument time is not provided, the ordinary
square-root transformation is calculated.
-
p2asin():
- new argument
n to calculate Freeman-Tukey double arcsine transformation
-
transf():
- new arguments
n and time to pass these argument to p2asin() or
ir2ft() for sm = "PFT" or sm = "IRFT"
- new arguments
n and time precede arguments func and args,
matching the argument order of backtransf()
-
settings.meta():
- new arguments
main.prefix, col.main, just.main, xpos.main,
gap.main, lineheight.main, fs.main, and ff.main to define defaults
for the main title of a forest plot
-
forest.meta(), settings.meta():
- font face arguments
ff.xyz are checked against values accepted by
grid::gpar() and also allow integer values 1 to 4
Bug fixes
-
forest.meta():
- do not automatically attach
label.e to the column n.e with
sample sizes for meta-analysis objects created with metagen() if
sample sizes in control group (n.c) are not provided
- print "IV" instead of "MH" for meta-analysis with binary outcome
using the Mantel-Haenszel method, but only printing the results for the
random effects model
(issue #93)
- print "SSW" or "LRP" instead of "NA" for meta-analysis with binary outcome
using the sample size method or a logistic regression with penalised
likelihood
(issue #93)
- print labels defined in
metarate() for meta-analysis of single incidence
rates (issue #97)
- show labels on the correct positions if argument
backtransf = FALSE for
meta-analyses conducted with metamean(), metaprop(), or metarate()
- show labels on the correct positions if argument
backtransf = TRUE and
argument pscale or irscale is used for meta-analyses conducted with
metaprop() or metarate()
- print "lnVR" and "SE(lnVR)" instead of "VE" and "SE(VE)" in forest plots
for meta-analysis objects created with
metagen(sm = "VE")
(issue #98)
- correctly clip diamonds for pooled estimates if argument
xlim excludes
the pooled estimate but includes one confidence limit
- automatically accounts for the widths of x-axis tick labels, input to
arguments
smlab, xlab, label.left, and label.right when calculating
forest plot spacing. User-specified values for arguments
colgap.forest.left and colgap.forest.right take precedence over the
automatic calculation
-
bubble(), forest.meta(), metabin(), metagen(), metainc(),
metaprop(), metarate(), print.meta(), print.summary.meta(), rd(),
trimfill(), update.meta():
- reject missing values in arguments
pscale and irscale
-
forest.metacum(), forest.metainf():
- show prediction intervals if argument
layout = "BMJ"
(issue #96)
- print number of events per number of observations or person-time instead of
proportions or rates
(issue #106)
-
metaprop(), metarate():
- use the harmonic mean of sample sizes or times to transform the null effect
for Freeman-Tukey transformed proportions (
sm = "PFT") or rates
(sm = "IRFT")
(issue #102)
- respect argument
exclude when calculating the harmonic mean used to back
transform Freeman-Tukey transformed proportions (sm = "PFT") or rates
(sm = "IRFT")
- calculate harmonic means for Freeman-Tukey transformed proportions
(
sm = "PFT") or rates (sm = "IRFT") using only non-excluded studies with
both event counts and sample sizes or exposure times available
(pull #107)
-
metacont(), metamean():
- correctly identify studies with non-positive sample sizes or means
(issue #103)
-
metagen():
- correctly transform
null.effect when argument transf = FALSE
- do not consider studies with infinite treatment estimates or standard
errors in meta-analysis calculations
(issue #103)
-
print.meta(), forest.meta():
- correctly back-transform
null.effect from metagen() objects when
argument backtransf = TRUE
-
metacum(), metainf(), subgroup():
- correctly preserve all user-specified analysis settings and study-level
information when reconstructing analyses for binary, continuous,
incidence rate, proportion, rate, and generic meta-analyses
-
metacum(), metainf():
- preserve method details supplied to
metacont() for standardized mean
differences, including method.smd, sd.glass, exact.smd, and
pooledvar
- preserve the value of
irunit supplied to metarate()
-
subgroup():
- correctly use subgroup harmonic exposure times for back-transformation
of IRFT common-effect, random-effects, and prediction results
(pull #107)
- preserve user-specified common-effect and random-effects weights
- preserve the specified null effect for all supported meta-analysis types
-
summary.meta():
- correctly identify PFT and IRFT meta-analysis objects and use the
corresponding summary branches
(pull #107)
-
settings.meta():
- reject
NULL for numeric settings where NULL is not an admissible value
-
pairwise():
- consider continuity correction in binary outcomes with summary measure
"DOR" or "VE" (issue #94)
-
labbe():
- show common effect / random effects lines for
sm = "VE"
(issue #94)
-
drapery():
- bug fix for erratic prediction region if the x-limits are too narrow
- back transform results for vaccine efficacy (
sm = "VE")
(issue #94)
-
bubble():
- back transform results for vaccine efficacy (
sm = "VE")
(issue #94)
- back transform results for Freeman-Tukey transformed proportions
(
sm = "PFT") or rates (sm = "IRFT") using study-specific sample
sizes or times for individual studies and the corresponding harmonic mean
for the meta-regression line
(issue #102)
- print the correct y-axis label if
pscale or irscale differs from 1
(issue #105)
-
metabias():
- use efficient score for risk ratio instead of odds ratio in meta-analysis
with binary outcome and vaccine efficacy (
sm = "VE")
(issue #94)
-
cidprop():
- transform decision thresholds for Freeman-Tukey transformed proportions
(
sm = "PFT") or rates (sm = "IRFT") using the harmonic mean of sample
sizes or times
(issue #102)
-
plot.cidprop():
- back transform results for vaccine efficacy (
sm = "VE")
(issue #94)
- input to arguments
random and prediction was ignored
- input to argument
xlim determines the limits of the x-axis
(issue #94)
-
estimates():
- return correct order of lower and upper confidence limits for
sm = "VE" and backtransf = TRUE
(issue #94)
-
blup.meta(), print.blup.meta():
- return correct order of lower and upper confidence limits for
sm = "VE"
(issue #94)
-
ciClopperPearson(), ciPoisson():
- calculate confidence intervals only when both event counts and sample sizes
or exposures times are available; otherwise return missing intervals
(pull #107)
Internal changes
-
Use R package testthat for unit tests.
-
R package testthat added to Suggests.
-
New internal function layout_colors() to define default colours for forest
plots.
-
New internal functions chknumeric_strict() and chkfontface() to check
numeric arguments without missing or NULL values or font face arguments
-
New internal function warn_ignore_dots() to provide consistent warnings for
ignored arguments supplied via ....
-
New internal function percent_label() to format percentage labels.
-
chkchar(), chkcolor(), chklevel(), chknumeric():
- removed deprecated argument
single; replaced by argument length
-
forest.meta():
- removed obsolete arguments
bmj.xpos and rob.xpos; a warning is printed
if either is used and argument warn.deprecated = TRUE
-
cidprop():
- for vaccine efficacy (
sm = "VE"), defaults for cid.below.null and
cid.above.null calculated from cid are based on relative instead of
absolute distances from the null effect
(issue #94)
-
metaprop(), metarate():
- store harmonic mean of sample sizes or times for Freeman-Tukey transformed
proportions (
sm = "PFT") or rates (sm = "IRFT")
-
trimfill():
- use ordinary arcsine transformation logic for Freeman-Tukey double arcsine
transformed proportions (
sm = "PFT") and ordinary square root
transformation logic for Freeman-Tukey transformed rates (sm = "IRFT")
because harmonic mean changes with filled studies
-
crtitle():
- new arguments
prefix and forest
-
formatN(), pasteCI():
- argument
text.NA renamed to lab.NA
meta 8.5-0 (2026-05-25)
Major changes
-
By default, the width and height of a file to store a forest plot is
automatically determined
(issues #86). Furthermore, the user
can specify the height of the file with the forest plot.
-
Nour Edin Darwish [email protected] added as co-author or R
functions forest.meta() and author of forest_dims().
-
For generalised linear mixed models, the number of studies included in the
meta-analysis is extracted from rma.glmm() in R package metafor.
-
R package cli added to Depends.
-
R package svglite added to Suggests.
User-visible changes
Bug fixes
-
forest.meta():
- remove duplicate columns from forest plots with risk of bias assessment if
argument 'rob.only = TRUE'
- argument 'rightlabs' can be used in forest plots with risk of bias
assessment (note, column names for risk of bias domains cannot be changed
with this argument)
(issue #88)
-
read.cdir():
- add missing information on subgroups
(no subgroup meta-analysis was conducted)
- fix errors due to changes in Cochrane review data format
Internal changes
- metabin(), metainc(), metaprop(), metarate():
- list element 'k' (number of studies in meta-analysis) is taken from
rma.glmm() in R package metafor
meta 8.3-0 (2026-04-02)
Major changes
-
Relax the minimum number of studies in a meta-analysis required to calculate
confidence and prediction intervals
(issue #80):
- calculate confidence interval for tau2 and tau for two or more studies
(was more than two studies)
- calculate Hartung-Knapp prediction interval
(argument 'method.predict = "HK"') for two or more studies
(was more than two studies)
- calculate Partlett and Riley prediction interval
(argument 'method.predict = "HK-PR"') for three or more studies
(was more than three studies)
-
Calculate confidence for I2 and H if argument 'method.I2 = "tau2"'
(issue #80).
-
More flexible definition of column labels in forest plots
(issue #87).
-
New function rd() to calculate risk difference(s) from meta-analysis results;
results are expressed as absolute risk reduction / increase or absolute
benefit increase / reduction.
-
R function cidprop() uses null effect as threshold, if defined.
-
R function pairwise() accepts data in the common BUGS format, i.e.,
relative treatment effects in comparison to a reference treatment.
-
For relative effect measures show "ln" instead of "log" in printouts and
forest plots if 'backtransf = FALSE'.
-
R package metabook added to Depends (to access meta-analysis datasets).
User-visible changes
Bug fixes
-
forest.meta():
- reference line and CID lines had wrong length in forest plots with
risk of bias information and without overall heterogeneity statistics
(issue #84)
- remove extraneous "^2" from method details for confidence of tau2
(issue #87)
-
forest.metainf():
- input to arguments 'prediction', 'overall', and 'backtransf' was
ignored
(issue #83)
-
forest.metabind():
- input to argument 'col.square' was ignored for square colour
(issue #81)
meta 8.2-1 (2025-09-01)
Major changes
- More flexible printing of treatment labels in forest plots provided in
arguments 'label.e' and 'label.c'
User-visible changes
- forest.meta():
- new arguments 'just.label.e' and 'just.label.c' to define the justification
of treatment labels
- arguments 'label.e.attach' and 'label.c.attach' can be vectors to define
columns to print treatment labels
Bug fixes
meta 8.2-0 (2025-07-23)
Major changes
-
Inverse variance heterogeneity (IVhet) method by
Doi et al. (2015) going
back to Henmi and Copas (2010)
implemented.
-
User-defined weights can be provided in meta-analysis functions.
-
Major revision of R function metaadd() to add meta-analysis results to
existing meta-analysis object.
-
R function longarm() can be used with dose-response data.
Bug fixes
User-visible changes
-
metabin(), metacont(), metacor(), metagen(), metainc(), metamean(),
metaprop(), metarate(), update.meta():
- new argument 'method.common.ci' to choose IVhet method
- new arguments 'weights', 'weights.common', and 'weights.random' to provide
user-defined weights
-
metaadd():
- argument 'type' can be equal to 'tau2' to provide estimate for the
between-study variance (argument 'TE') and its confidence interval
(arguments 'lower' and 'upper')
- new argument 'se' to provide standard error
- new argument 'df' to provide degrees of freedom for random effects estimate
or prediction interval
- argument 'method' replaces arguments 'method.common', 'method.random',
'method.tau' and 'method.predict'
- argument 'method.ci' replaces argument 'method.random.ci'
-
longarm():
- new arguments 'agent1', 'agent2', 'dose1', 'dose2', and 'sep.ag' for
dose-response data
-
forest.meta(), settings.meta():
- new argument 'cid.pooled.only' to restrict CID region to meta-analysis
results
meta 8.1-0 (2025-05-02)
Major changes
-
New functions cidprop() and plot.cidprop() to calculate and plot
expected proportions of comparable studies with clinically important benefit
or harm which are derived from the prediction interval.
-
Rewrite of R function metacum() for cumulative meta-analysis with dedicated
print and forest functions.
-
Rewrite of R function metainf() for leave-one-out meta-analysis with dedicated
print and forest functions.
-
Remove R code for cumulative or leave-one-out meta-analysis from R function
forest.meta().
-
In forest plots, information for additional columns can be printed in the
lines with pooled effects using the new argument 'data.pooled'.
-
R packages *ggplot2, tibble, and scales added to Imports.
-
R packages gridExtra and ggpubr added to Suggests.
Bug fixes
-
forest.meta():
- consider setting for list element 'null.effect' for metamean(), metaprop()
and metarate() objects to fix
(issue #67)
- remove duplicated columns from forest plots with RevMan5 layout and risk of
bias information
- use correct column labels for log transformed treatment estimates and
standard errors (list elements TE and seTE) if argument 'backtransf = TRUE
-
update.meta():
- consider setting for list element 'rho' for metabin(), metacor(),
metainc(), metamean(), metaprop(), metarate()
-
metabin(), metacont(), metacor(), metainc(), metamean(), metaprop(),
metarate():
- bug fix for three-level model if argument 'detail.tau' is not specified by
the user
-
Fix bug 'could not find function "func"' in internal function chksuitable()
User-visible changes
-
metabin(), metainc():
- new arguments 'incr.e' and 'incr.c' for user-specified continuity correction
- do not warn about continuity correction for generalised 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.right' to fix
(issue #66)
-
metabin(), metacont(), metacor(), metainc(), metamean(), metaprop(),
metarate(), update.meta():
- new argument 'detail.tau'
-
forest.meta():
- argument 'lower.equi' has been replaced by 'cid.lower'
- argument 'upper.equi' has been replaced by 'cid.upper'
- argument 'lty.equi' has been replaced by 'lty.cid'
- argument 'col.equi' has been replaced by 'col.cid'
- new argument 'cid' which can be used instead of 'cid.lower' and 'cid.upper'
- new arguments 'fill.cid', 'fill.cid.lower' and 'fill.cid.upper' to colour
regions of clinically important differences
- new argument 'data.pooled' to add information
-
metacum(), metainf():
- new arguments 'prediction', 'overall', and 'text.pooled'
- new arguments 'cid', 'cid.lower', and 'cid.upper' to define CID thresholds
- new argument 'small.values' to specify whether small treatment
effects indicate a beneficial or harmful effect
-
settings.meta():
- new settings 'cid', 'cid.lower', 'cid.upper', 'lty.cid', 'col.cid',
'fill.cid', and 'digits.cid'
Internal changes
meta 8.0-2 (2025-01-21)
Bug fixes
-
update.meta():
- Fix bug in setting method.sd for metacont update
(pull #63)
-
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 penalised 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 recognised 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 '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) tau2 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 a change in the default settings of 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 replaced by 'col.subgroup',
- argument 'bysort' has been replaced by '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 replaced by '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' replaced by '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
(issue #42)
-
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' replaced by 'digits.stat'
and 'print.stat'
-
print.summary.meta(), settings.meta():
- argument 'digits.zval' replaced by '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' replaced by '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 I2
with fixed effect results and information on tau2 and tau with
random effects results (previously, information on Q, I2, tau2,
and tau 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' replaced by '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
tau2
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 standardised 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: I2, 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 I2, tau2, 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' replaced by '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' replaced by '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 Freeman-Tukey 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' replaced by '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 and 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)