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 data set was
provided as input to argument ‘id’ in metacont()
Argument ‘tau.common = TRUE’ was ignored in subgroup analysis of
three-level model in metacont()
Argument ‘level’ was ignored in the calculation of confidence
limits for individual studies in metacont() and metamean() if argument
‘method.ci = “t”’
Show correct studies in forest plot with subgroups and missing
treatment effects if argument ‘allstudies = FALSE’
Show points in bubble plot of meta-regression with GLMM
User-visible changes
For three-level models,
- argument ‘id’ has been renamed to ‘cluster’,
- cluster variable is shown in forest plots.
New arguments ‘common’ and ‘cluster’ in functions metabin(),
metacont(), metacor(), metagen(), metainc(), metamean(), metaprop() and
metarate()
New function subset.longarm() to select subset of a longarm
object
New argument ‘method.ci’ in function metarate()
New argument ‘method.ci.rate’ in function
settings.meta()
New argument ‘method.incr’ in functions metabin(), metainc(),
metaprop() and metarate()
print.summary.meta():
- for a single study and metabin() with method = “MH”, sm = “RR” and
RR.Cochrane = FALSE, print results using a continuity correction for
sample sizes of 1x incr (individual study) and 2x incr (meta-analysis of
single study)
Internal changes
forest.meta():
- use meta:::formatN() instead of format() for formatting
- print study label “1” instead of “” for a single study
metarate():
- list elements ‘lower’ and ‘upper’ contain untransformed confidence
limits for individual studies
New internal function update_needed() to check whether update of
meta object is needed
metabin(), metacont(), metacor(), metagen(), metainc(),
metamean(), metaprop() and metarate():
- new list element ‘k.TE’ with number of estimable effects
Major changes
Forest plot for meta-analysis with subgroups:
- more flexible printing of subgroup results
- by default, do not show subgroup results (pooled estimates and
information on heterogeneity) for subgroups consisting of a single
study
Prediction intervals in subgroups can be shown independently of
prediction interval for overall meta-analysis in printouts and forest
plots
Bubble plot shows relative treatment effects on original scale
instead of log scale and reference line is shown
Trim and fill, limit meta-analysis and Copas selection model
objects can be used in function metabind()
New function longarm() to transform data from pairwise
comparisons to long arm-based format
New auxiliary function labels.meta() to create study labels for
forest plots in JAMA or Lancet layout
Printing of spaces in confidence intervals can be
suppressed
Help page of forest.meta() updated
Bug fixes
Use correct standard error to calculate prediction interval if
Hartung-Knapp method was used
In forest plots, show correct degrees of freedom for test of
effect in subgroups for Hartung-Knapp method
In update.meta(), consider input for arguments ‘pscale’,
‘irscale’ and ‘irunit’ for meta-analysis objects created with
metagen()
User-visible changes
- forest.meta():
- new argument ‘subgroup.hetstat’
- arguments ‘subgroup’, ‘subgroup.hetstat’, ‘prediction.subgroup’,
‘test.effect.subgroup’, ‘test.effect.subgroup.fixed’ and
‘test.effect.subgroup.random’ can be a logical vector of same length as
number of subgroups
- arguments ‘lab.e’, ‘lab.c’, ‘lab.e.attach.to.col’ and
‘lab.c.attach.to.col’ renamed to ‘label.e’, ‘label.c’, ‘label.e.attach’
and ‘label.c.attach’
- forest.meta(), metabin(), metacont(), metacor(), metacr(),
metagen(), metainc(), metamean(), metaprop(), metarate(), print.meta(),
update.meta():
- new argument ‘prediction.subgroup’
- metamerge():
- first argument can be of class ‘limitmeta’ or ‘copas’
- bubble.metareg():
- new argument ‘backtransf’ to (not) back transform relative treatment
effects on y-axis
- new arguments ‘ref’, ‘col.ref’, ‘lty.ref’ and ‘lwd.ref’ for
reference line
- settings.meta():
- arguments ‘print’, ‘reset’ and ‘setting’ can be used like any other
setting; for example, it is possible to fully reset the settings and
switch to the RevMan 5 settings
- R commands ‘settings.meta(“print”)’ and ‘settings.meta()’ produce
the same printout
- new global setting ‘prediction.subgroup’ for prediction intervals in
subgroups
- new global settings ‘CIlower.blank’ and ‘CIupper.blank’
- cilayout():
- new arguments ‘lower.blank’ and ‘upper.blank’ to suppress printing
of spaces in confidence intervals
- additional checks for length of arguments
Internal changes
Major changes
- For meta-analysis of single proportions,
- export p-value of exact binomial test for individual studies if
Clopper-Pearson method (method.ci = “CP”) is used to calculate
confidence intervals for individual studies
- do not export p-value for individual studies if argument ‘method.ci’
is not equal to “CP” or “NAsm” (normal approximation based on summary
measure)
Bug fixes
Meta-analysis of continuous outcomes using Hedges’ g or Cohen’s d
as summary measure resulted in inestimable SMDs in
individual studies if the total sample size was larger than 343 and
argument ‘exact.smd’ was TRUE (default)
Forest plot creation for meta-analysis of single means with
subgroups resulted in an error
Internal changes
New internal function ciClopperPearson() to calculate confidence
limits and p-value for exact binomial method
Exported list elements changed for internal functions
ciAgrestiCoull(), ciSimpleAsymptotic() and ciWilsonScore()
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
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
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
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
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
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 data set
(list element ‘data’)
- new logical list element ‘three.level’ indicating whether
three-level model was used
Bug fixes
- For argument ‘adhoc.hakn = “ci”’, directly compare width of
confidence intervals of Hartung-Knapp method and classic random effects
meta-analysis
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”’
Major changes
- Prediction intervals for subgroups implemented
Bug fixes
- metacont():
- use correct variance formula for Glass’ delta
- metainc():
- update command resulted in an error Arguments ‘event.e’ and
‘n.e’ must have the same length for meta-analysis with subgroups
(due to list elements ‘n.e.w’ and ‘n.c.w’ which were interpreted as
‘n.e’ and ‘n.c’ containing missing values instead of being NULL)
- print.meta():
- use of argument ‘details = TRUE’ resulted in an error in
meta-analyses with duplicated study labels
- Consider argument ‘adhoc.hakn’ to calculate confidence intervals in
random effects subgroup meta-analyses
User-visible changes
- print.meta():
- column with information on subgroups added to details if argument
‘details = TRUE’
- forest.meta():
- new argument text.predict.w’ to label the prediction interval in
subgroups
- arguments ‘text.fixed.w’ and ‘text.random.w’ checked for correct
length
- Ad hoc variance correction for Hartung-Knapp method not
available for GLMMs
Internal changes
- metacont():
- get rid of warnings ‘Unknown or uninitialised column’ if argument
‘subset’ is used
- subgroup():
- calculate prediction intervals for subgroups
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
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”’
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)
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()
Bug fixes
- metacr():
- set summary measure to “OR” for Peto odds ratio
Major changes
Deeks’ linear regression test for funnel plot asymmetry of funnel
plots of diagnostic test accuracy studies implemented (Deeks et.,
2005)
Effective sample size (Deeks et.,
2005) can be used on y-axis of funnel plot
Discard infinite estimates and standard errors from calculation
of heterogeneity measures
Diagnostic odds ratio (sm = “DOR”) added as new effect measure in
metabin() and metagen()
User-visible changes
forest.meta(), forest.metabind():
- arguments ‘digits.zval’ and ‘print.zval’ renamed to ‘digits.stat’
and ‘print.stat’
print.summary.meta(), settings.meta():
- argument ‘digits.zval’ renamed to ‘digits.stat’
metacr():
- do not print a warning for inverse variance meta-analysis with
binary outcome
Help page for tests of funnel plot asymmetry updated
Help pages for metabin() and metainc() updated
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’ is 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 to import RevMan 5 analysis datasets:
- extract_outcomes(), oct2txt(), read.rm5.rm5()
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, will 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, will be removed in a future
update)
Internal functions TE.seTE.iqr.range(), TE.seTE.iqr() and
TE.seTE.range() renamed to mean.sd.iqr.range(), mean.sd.iqr() and
mean.sd.range()
mean.sd.iqr.range():
- new arguments ‘method.mean’ and ‘method.sd’
mean.sd.iqr(), mean.sd.range():
- new argument ‘method.mean’
chkchar(), chkcolor(), chklevel(), chknumeric():
- argument ‘single’ renamed to ‘length’ (which can be used to test for
a specific vector length instead whether it is a single value) (argument
‘single’ is still available for backward compatibility, however, will be
removed in a future update)
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
(conflicts with metafor)
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
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 I-squared of
residual heterogeneity in meta-analysis with subgroups (instead of
likelihood-ratio Q statistic)
Bug fixes
User-visible changes
- forest.meta():
- possible to print results for test of an overall effect or subgroup
differences even if meta-analysis results are not shown
- new defaults for arguments ‘overall’ and ‘overall.hetstat’ (which
are now considered from meta-analysis objects)
- print.summary.meta():
- for meta-analysis with subgroups, print information on Q and I^2
with fixed effect results and information on tau and tau^2 with random
effects results (previously, information on Q, I^2, tau, and tau^2 was
reported twice)
Internal changes
- do not calculate confidence limits for tau2 and tau in intermediate
calculations of other quantities (i.e., use argument method.tau.ci =
““)
Major changes
- New function drapery() to generate a drapery plot (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())
Bug fixes
- forest.meta():
- printing an additional column on the right side of the forest plot
does not result in an error (bug was introduced in
meta, version 4.9-8)
User-visible changes
- labbe():
- new argument ‘pos.studlab’
- argument checks implemented
- baujat(), bubble():
- argument ‘pos’ renamed to ‘pos.studlab’
- argument checks implemented
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
Major changes
- Subgroup analysis using argument ‘byvar’ possible for generalised
linear mixed models (GLMMs)
Bug fixes
- metaprop():
- no error if argument ‘tau.common’ is TRUE for GLMM
- metabin(), metainc(), metarate():
- consider argument ‘control’ in subgroup analysis
User-visible changes
- Major update of help pages:
- metabin(), metagen(), metainc(), metaprop(), metarate()
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
- ciAgrestiCoull():
- set lower confidence limit to 0 for negative values
- set upper confidence limit to 1 for values above 1
- subgroup meta-analyses return new list element ‘pval.Q.w’ (change in
internal function subgroup())
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
- metagen():
- new arguments ‘pval’, ‘df’, ‘lower’, ‘upper’, ‘level.ci’, ‘median’,
‘q1’, ‘q3’, ‘min’, ‘max’, ‘approx.TE’, ‘approx.seTE’ to approximate
treatment estimates and / or standard errors from other information
- forest.meta():
- printing of leading zeros in p-values can be suppressed (new
argument ‘zero.pval’)
- rounding of values for additional numerical columns possible (new
arguments ‘digits.addcols’, ‘digits.addcols.left’, and
‘digits.addcols.right’)
- argument ‘big.mark’ is considered for additional columns
- new arguments ‘type.subgroup.fixed’, ‘type.subgroup.random’, and
‘lab.NA.weight’
- settings.meta(), gs():
- argument names can be abbreviated
- Major update of help pages of metagen() and metaprop()
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 and / 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
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’ is
FALSE
Major changes
- New argument ‘control’ in meta-analysis functions which is passed on
to R function rma.uni() or rma.glmm() from R package
metafor to control the iterative process to estimate
the between-study variance tau^2
User-visible changes
- metabin(), metacont(), metacor(), metagen(), metainc(), metamean(),
metaprop(), metarate(), update.meta():
- new argument ‘control’ (see major changes)
- forest.meta():
- new argument ‘calcwidth.subgroup’
Bug fixes
- bubble.metareg():
- ignore missing values in covariate to calculate limits on
x-axis
- works if data set used to create meta-analysis object is a tibble
instead of a data frame
Internal changes
- metabind():
- argument ‘tau.common’ only considered for subgroup analyses
- hetcalc():
- argument ‘control’ passed on to R function rma.uni() from R package
metafor
- metacum(), metainf(), subgroup():
- argument ‘control’ from meta-analysis objects considered
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()
Major changes
Subgroup results consider the exclusion of individual studies
(bug fix)
For generalized 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
- print.summary.meta():
- print information on Generalized Linear Mixed Model (GLMM) for
metarate() objects
- print information on increments added to calculate confidence
intervals for individual studies (for metarate() with GLMM)
- funnel.meta():
- new arguments ‘ref.triangle’, ‘lty.ref’, ‘lwd.ref’, ‘col.ref’, and
‘lty.ref.triangle’ to add reference value (null effect) and
corresponding confidence intervals to the funnel plot
- metabin():
- new argument ‘pscale’ to change printout of risk differences
- metainc():
- new arguments ‘irscale’ and ‘irunit’ to change printout of incidence
rate differences
- forest.meta(), print.meta(), print.summary.meta(), update.meta():
- consider arguments ‘pscale’, ‘irscale’, and ‘irunit’ for
meta-analysis objects created with metabin() and metainc()
- print.meta():
Internal changes
- metaprop():
- for random effects model, rma.glmm() from package
metafor is called internally with argument ‘method =
“FE”’ if only a single study is available
- metareg():
- for generalised linear mixed models, fallback to fixed effect model
if number of studies is too small for random effects
meta-regression
- asin2ir():
- back-transformation could result in (very small) negative zero
values due to imprecisions (-1e-19); these values are set to zero
now
- subgroup():
- code for metamean() added
- chkchar():
- new argument ‘nchar’ to test the length of character string(s)
- New internal function is.untransformed() to check for effect
measures without (back-)transformation
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 for the
number 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)
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 is 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
Major changes
Similar to RevMan 5, individual studies can be excluded from
meta-analysis, however, will be shown in printouts and forest
plots
In forest plots, line spacing can be determined by the
user.
User-visible changes
metabin(), metacor(), metacont(), metagen(), metainc(),
metaprop(), metarate():
- new argument ‘exclude’ to exclude studies from meta-analysis
forest.meta():
- new argument ‘spacing’ to determine line spacing
- bug fix for for meta-analysis with standardized mean difference (sm
= “SMD”) and argument layout = “RevMan5”
R function ci() can be used with vectors or matrices of treatment
estimates and standard errors and a single value for argument ‘df’,
i.e., degrees of freedom (which is used in R package
netmeta to calculate prediction intervals for network
meta-analysis estimates)
metacum(), metainf():
- argument ‘null.effect’ considered internally for objects generated
with metacor(), metagen(), metaprop() and metarate()
Internal changes
- baujat.meta(), metabias.meta(), metacum(), metainf(), forest.meta(),
funnel.meta(), metareg(), print.meta(), radial.meta(), trimfill.meta(),
update.meta():
- changes to deal with excluded studies
Major changes
Calculate confidence interval for I-squared 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
User-visible changes
- metacum(), metainf():
- bug fix for meta-analysis objects without continuity correction,
i.e., metacont(), metacor(), metagen() (bug was introduced in version
4.8-0 of meta) Error message: “Error in rep_len(x$incr,
k.all): cannot replicate NULL to a non-zero length”
- bug fix for metarate() objects (improper use of metaprop()
internally)
Major changes
- Continuity correction can be specified for each individual study in
meta-analysis with proportions or incidence rates
User-visible changes
- metabin(), metainc(), metaprop(), metarate():
- argument ‘incr’ can be of same length as number of studies in
meta-analysis
- metaprop():
- bug fix in studies with missing information for events or sample
size and argument method.ci = “CP”
- bug fix such that test for an overall effect is actually
calculated
- forest.meta():
- bug fix such that summary label (argument ‘smlab’) is printed above
forest plot if argument ‘fontsize’ is unequal to 12
- by default, label on x-axis and text on top of forest plot are
printed in center of forest plot (arguments ‘xlab.pos’,
‘smlab.pos’)
- print.summary.meta():
- print number of studies for fixed effect meta-analysis using
Mantel-Haenszel method if different from number of studies in random
effects model (only if summary measure is “RD” or “IRD” and at least one
study has zero events)
- metainc():
- bug fix such that argument ‘incr’ is considered for incidence rate
difference (sm = “IRD”)
Internal changes
act on NOTE in ‘R CMD check … –as-cran’ with R version, 3.4.0,
i.e. 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 tau^2 as well as H and I^2 to NA if only a single study
contributes to meta-analysis (e.g., if other studies in meta-analysis
have zero standard error)
updateversion():
- use R function update.meta() if version of meta
used to create R object is below 3.2
Major changes
Null hypothesis for test of an overall effect can be specified
for metacor(), metagen(), metaprop(), and metarate(); for all other
meta-analysis functions implicit a null effect of zero is assumed (for
relative effect measures, e.g., odds ratio and hazard ratio, the null
effect is defined on the log scale)
User can choose whether to print the following heterogeneity
quantities: I^2, H, Rb (by default, heterogeneity measure Rb is not
printed and thus revoking a change in meta,
4.7-0)
In forest plots with subgroups, study weights are summed up to
100 percent within each subgroup if no overall estimates are requested,
i.e., argument overall is FALSE (like before, by default, weights are
not printed if argument overall is 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 and addrow are 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, print.Rb to specify heterogeneity
measures shown in output
- new arguments text.tau2, text.I2, text.Rb to change text printed to
identify respective heterogeneity measure
- only print information on double zero studies if argument allstudies
is 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,
text.Rb to modify printing of heterogeneity measures
Internal changes
- summary.meta():
- bug fix: list element ‘ircale’ renamed to ‘irscale’
- list element ‘within’ removed which has not been used since
meta, version 1.1-4
Major changes
Forest plots:
- forest plots with RevMan 5 and JAMA layout
- use of mathematical symbols for I^2, tau^2, etc.
- individual study results can be omitted from forest plot (especially
useful to only print subgroup results)
- labels can be printed at top of forest plot
Measure of between-study heterogeneity added:
Default settings of meta-analysis methods specified via gs()
instead of extracting elements of list .settings (which makes output of
args() easier to read, e.g., args(metabin))
Version of suggested R package metafor must be
at least 1.9-9 (due to change in arguments of rma.uni() and
rma.glmm())
User-visible changes
forest.meta():
- argument layout:
- new layouts: “JAMA” to produce forest plots with JAMA
style
- RevMan 5 layout extended
- arguments can be specified without using grid::unit(): plotwidth,
colgap, colgap.left, colgap.right, colgap.studlab, colgap.forest,
colgap.forest.left, colgap.forest.right
- new argument study.results to print (default) or omit individual
study results from forest plot
- new argument bottom.lr to change position of labels on left and
right side of forest plot
- new arguments col.label.right and col.label.left to change colour of
labels on left and right side of forest plot
- argument weight renamed to weight.study and new argument
weight.subgroup added to specify whether plotted subgroup results should
be of same or different size
- new arguments print.Rb, print.Rb.ci, Rb.text for heterogeneity
measure Rb
- new arguments to control printing: digits.cor, digits.mean,
digits.sd, digits.time, digits.zval
- new argument print.subgroup.labels to print (default) or omit rows
with subgroup label from forest plot
- new argument type.subgroup to change plotting of subgroup
results
- argument addspace renamed to addrow
- new argument addrow.subgroups to add a blank line between subgroup
results
- new argument addrow.overall to add a blank before meta-analysis
results
- new argument blanks to enhance printing of test statistics,
heterogeneity measurs, 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 (these arguments 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 new arguments: smrate, layout
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 arcsin transformation and
backtransformation slightly changed in meta-analysis of single
proportions
By default, do not print a warning if backtransformation 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 (if argument sm = “ROM”)
metaprop():
- change in Freeman-Tukey double arcsin 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():
- print correct results for subgroup analyses of metaprop objects with
sm = “PFT” (bugfix in internal subgroup() function)
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
backtransformed 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 backtransform arcsine transformed
incidence rates
backtransf(), catmeth(), metacum(), metainf(), subgroup(),
xlab():
- extension to handle meta-analysis objects created with
metarate()
metaprop(), asin2p():
- calculation of Freeman-Tukey double arcsin transformation changed
such that sm = “PFT” and sm = “PAS” result in similar estimates (TE,
TE.fixed, TE.random), i.e. values are multiplied by 0.5 for sm =
“PFT”
subgroup():
- bux fix in calculation of harmonic mean of sample sizes (for
metaprop objects with sm = “PFT”) and event times (for metarate objects
with sm = “IRFT”)
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, the pscale argument 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
- the following arguments have been renamed (old arguments 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 (use squares or
diamonds to plot treatment effects and confidence intervals) .
col.inside.fixed, col.inside.random (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 (print results for test of treatment effect in
subgroups)
- bug fix: reference line and lines for fixed effect and random
effects estimate were too short if test.overall is TRUE
- bug fix: arguments lab.e.attach.to.col and lab.c.attach.to.col were
ignored for R objects created with metagen()
- metabin(), metacont(), metacor(), metagen(), metainc(), metaprop(),
forest.meta(), print.summary.meta(), summary.meta(), update.meta(),
settings.meta():
- 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 (see argument
backtransf)
- 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
User-visible changes
- metareg(), update.meta():
- bug fix such that use of these functions with metaprop objects using
argument method = “GLMM” does not result in an error
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 method argument and
model.glmm argument (not used in metaprop function)
- 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() () not considered for GLMMs
- 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
- labels argument can be used instead of label argument to change
labels on x-axis (axis() uses labels argument)
- 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
tau-squared is set equal to 0)
- New list elements:
- model.glmm, .glmm.fixed, .glmm.random, version.metafor in metabin(),
metainc(), metaprop()
- doublezeros in metabin() - only for odds ratio and risk ratio
- allstudies, doublezeros, model.glmm, .glmm.fixed, .glmm.random,
version.metafor in summary.meta()
- meta-internal():
- set defaults for new 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
- Function metacont:
- bug fix such that correct treatment estimates for individual studies
are calculated for Glass’s delta (i.e. arguments sm = “SMD” and
method.smd = “Glass”)
- Function metaprop:
- print correct error message if number of events is larger than
number of observations
- Function 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, tau-squared 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 such that studies with missing treatment effect and standard
error get zero weight in random effects meta-analysis
- do not stop estimation algorithm if estimated tau-squared is
negative
- Function settings.meta:
- bug fix such that no error occurs if function is used with an
unassigned argument
- Internal functions format.p and format.tau:
- new argument ‘digits’ to round p-values and tau-squared values
- Internal functions chkchar, chkclass, chklength, chklevel,
chklogical, chkmiss, chknull, chknumeric, setchar:
- new argument ‘name’ to change name of checked argument in
printout
- Help page of R function forest.meta updated
- Functions metabin, metainc, and metaprop:
- missing values are allowed in numbers of events or patients (studies
with missing values get zero weight in meta-analysis)
- Function forest.meta:
- print information on test for overall effect (see arguments
‘test.overall.fixed’ and ‘test.overall.random’)
- print information on test for subgroup differences in meta-analysis
with subgroups (see arguments ‘test.subgroup.fixed’ and
‘test.subgroup.random’)
- new argument ‘layout’ to change the layout of the forest plot
- argument ‘lab.NA’ considered for all columns in forest plot
(e.g. numbers of events and patients for metabin objects)
- new argument ‘lab.NA.effect’ to label NAs in individual treatment
estimates and confidence intervals
- bug fix such that no error occurs if random effects estimate is
missing
- Function metareg:
- additional arguments implemented (hakn, level.comb, intercept)
- argument ‘…’ is no longer ignored but passed on to R function
rma.uni (e.g., to control the iterative estimation process)
- bug fix such that a fixed effect meta-regression can be conducted
(argument method.tau=“FE”)
- Function metabin:
- use Inverse Variance instead of Mantel-Haenszel method if only a
single study has a non-missing treatment estimate or standard error
- Functions settings.meta and meta-internal:
- code added for new arguments in forest.meta function to print
information on tests
- Help pages:
- help page of R functions metareg and forest.meta updated
- link to RevMan webpage updated
Copyright changed (new names for Institute and Medical
Center)
Function 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
Function forest.meta:
- bug fix such that additional columns used in arguments leftcols and
rightcols are sorted appropriately if argument sortvar is not
missing
- prediction interval can be printed if random effects estimate is not
shown
- new argument print.I2.ci to print confidence intervals for
I-squared
Function print.meta and print.summary.meta:
- prediction interval can be printed if random effects estimate is not
shown
Functions settings.meta, meta-internal, catmeth and
update.meta:
- code added for new argument ‘exact.smd’ in metacont function
Functions ci and 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
- reflect changes in metacont function
- updated RevMan 5 reference
Title of R package changed
Function metacont:
- new argument ‘method.smd’ to implement Cohen’s d
(method.smd=“Cohen”) and Glass’ delta (method.smd=“Glass”) as additional
effect measures for the standardised mean difference (sm=“SMD”)
- new argument ‘sd.glass’ to choose the denominator for Glass’
delta
Function update.meta:
- new arguments ‘method.smd’ and ‘sd.glass’ added
Function summary.meta:
- information for new arguments ‘method.smd’ and ‘sd.glass’ added to
summary.meta object
Functions settings.meta and meta-internal:
- code added for new arguments ‘method.smd’ and ‘sd.glass’ in metacont
function
Function forest.meta:
- bug fix such that using this function with a metaprop object and
subgroups will not result in staggered point estimates
Function metagen:
- bug fix such that studies with missing treatment effect (argument
TE) but available standard error (argument seTE) get zero weight in
meta-analysis
Function paulemandel (used internally):
- only consider studies without missing treatment effect (argument TE)
and standard error (argument seTE) in calculation of between-study
variance tau-squared
Function chklevel (used internally):
- print meaningful error message if confidence limit is outside the
range (0, 1)
Function catmeth (used internally):
- print information on method to estimate the standardised mean
difference used in metacont function
Help pages of metacont and update.meta functions updated
- Function metabin:
- bug fix such that printing an R object created using the
Mantel-Haenszel and Peto method does not result in an error if any study
has zero events in both groups
- Function metabin:
- bug fix such that use of Peto method does not result in an
error
- argument ‘sm=“ASD”’ for arcsine difference instead of ‘sm=“AS”’
(abbreviations ‘sm=“AS”’ and ‘sm=“A”’ can be used as well)
- Functions metabin, metacont, metacor, metagen, metainc, and
metaprop:
- Weights w.random.w are calculated from random effects meta-analysis
ignoring subgroup membership (internally used function subgroup changed
accordingly)
- for subgroup analysis, argument ‘tau.common’ is set to TRUE if
argument tau.preset is not NULL
- Function forest.meta:
- bug fix such that function can be used with subgroups and additional
columns (arguments leftcols and rightcols)
Major revision
This update has been declared as major revision as R code to conduct
subgroup analyses has been moved from R functions summary.meta and
forest.meta to R functions metabin, metacont, metacor, metagen, metainc,
and metaprop. Accordingly, an R object generated with these functions
contains all results from subgroup analyses (see corresponding help
pages).
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 implented
in version 4.0-0 of meta.
Details
Function addvar has been removed from R package
meta (remaining functionality provided by forest.meta
function)
Function 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
Function bubble.metareg:
- bug fix such that bubble plot is generated for meta-regression
objects without intercept
- bug fix such that use of function does not result in an error for
some effect measures, e.g. sm=“RR”, “OR”, or “HR”
New R functions (used internally):
- subgroup, hetcalc
- updateversion
- bylevs, byvarname
- chkchar, chkclass, chklength, chklevel, chklogical, chkmetafor
chkmiss, chknull, chknumeric
- int2num, npn
- setchar, setstudlab
Functions format.p, format.tau, catmeth, and
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”
Functions print.summary.meta:
- remove code for R objects created with version 2.0-0 or lower of
meta
- print ‘p-value’ instead of ‘p.value’
Functions print.meta:
- print ‘p-value’ instead of ‘p.value’
Several help pages updated.
- Functions 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
- Functions print.meta, print.summary.meta:
- argument ‘logscale’ removed (replaced by argument ‘backtransf’)
- Functions print.summary.meta, forest.meta:
- print prediction interval for Freeman-Tukey double arcsin
transformation (sm=“PFT”, see help page on metaprop command)
- Function forest.meta:
- consider prediction interval to calculate limits on x-axis (if
argument ‘prediction=TRUE’)
- Function bubble.metareg:
- new argument ‘regline’ indicating whether regression line should be
added to plot
- Function settings.meta:
- new argument ‘print=TRUE’ to print listing of all settings (function
call without arguments does not print all settings any longer)
- a list with previous settings can be provided (see help page)
- New functions (used internally):
- backtransf (for back transformation of effect measures)
- is.relative.effect (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
- Function forest.meta:
- bug fix such that lower and upper confidence interval limits will be
sorted correctly if argument ‘sortvar’ is used (this bug has been
introduced in version 3.7-0 of meta)
- argument ‘sortvar’ works without reference to meta-analysis object,
e.g. command forest(meta1, sortvar=TE) can be used instead of
forest(meta1, sortvar=m1$TE) - see help page for examples.
- Help page of forest.meta function:
- examples using argument ‘sortvar’ added
- Function 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, pval.random set
to NA
- New functions:
- ciWilsonScore (used internally in metaprop function)
- ciAgrestiCoull (used internally in metaprop function)
- ciSimpleAsymptotic (used internally in metaprop function)
- estimate.missing (used internally in trimfill.default and
trimfill.meta; so far function was defined in both trimfill
functions)
- Function metacont:
- new argument ‘pooledvar’ to conduct meta-analysis of mean
differences (sm=“MD”) based on pooled variance for individual
studies
- Function 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 (fully functional)
- metacum (only upgrade to current version of meta)
- metainf (only upgrade to current version of meta)
- new arguments:
- method.ci (for metaprop objects)
- pooledvar (for metacont objects)
- left (for trimfill objects)
- ma.fixed (for trimfill objects)
- type (for trimfill objects)
- n.iter.max (for trimfill objects)
- new list element ‘call.object’, i.e call used to generate object
used as input to update.meta function
- Function as.data.frame.meta, baujat.meta, forest.meta, funnel.meta,
labbe.metabin, metacum, metainf, print.meta, summary.meta,
trimfill.meta:
- call update.meta function for meta-analysis objects created with
older meta packages (version < 3.7)
- Functions metabin, metacont, metacor, metagen, metainc, metaprop,
trimfill.default, trimfill.meta:
- new list elements: lower, upper, zval, pval (i.e. calculate
confidence limits as well as z- and p-values for individual
studies)
- Function print.meta and print.summary.meta:
- print information on method used for confidence intervals of
individual studies for metaprop objects
- Functions metacum and metainf:
- add calculations for metainc objects
- new list element ‘call’ with function call
- consider argument ‘pooledvar’ for metacont objects
- Functions 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
- New functions:
- baujat and baujat.meta (Baujat plot to explore heterogeneity in
meta-analysis)
- bubble and bubble.metareg (bubble plot to display the result of a
meta-regression)
- Function metareg:
- class ‘metareg’ added
- new list element .meta which is a list with information on
meta-analysis object used in function call
- Function update.meta:
- argument ‘studlab’ fully functional (I missed this argument in
version 3.2-0)
- Function print.meta:
- print study label for a single study in meta-analysis if argument
‘details=TRUE’ (internally function data.frame instead of cbind
used)
- New function is.installed.package (used internally)
- replacement for function is.installed.metafor
- Help pages datasets amlodipine and cisapride:
- execute examples for Hartung-Knapp method
- Help pages merged for the following commands:
- forest and forest.meta
- funnel and funnel.meta
- labbe and labbe.metabin
- metabias and metabias.meta
- trimfill and trimfill.meta
- Function metabin:
- Inverse variance method used instead of Mantel-Haenszel method if
argument ‘tau.common’ is TRUE
- Function metareg:
- tilde sign not necessary in argument ‘formula’ to make this function
more user friendly
- Function forest.meta:
- print common tau-squared for subgroups if argument tau.common is
TRUE in meta-analysis object
- Function 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’ is TRUE
- Functions metacor, metainc, and metaprop:
- arguments title, complab, and outclab part of R object
- Some help pages (slightly) updated.
New R function settings.meta to define and print default settings
for meta-analyses in R package meta
Function metagen:
- Hartung and Knapp method added (previously the rma.uni function from
R package metafor has been called for this method)
- Paule-Mandel method to estimate between-study variance implemented
using new internal function paulemandel which is based on R function
mpaule.default from R package metRology from S.L.R.
Ellison <s.ellison at lgc.co.uk> (Author of R function
mpaule.default is S. Cowen <simon.cowen at lgc.co.uk> with
amendments by S.L.R. Ellison)
Function metacont:
- studies with missing treatment estimate get zero weight in
meta-analysis
Functions metabin, metacont, metacor, metacr, metagen, metainc,
metaprop:
- default values changed according to R function settings.meta
Function metareg:
- use argument method.tau=“REML” if this argument is equal to “PM” for
meta-analysis object
Several help pages updated.
- Function forest.meta:
- bug fix such that correct confidence limits for individual studies
will be printed if argument ‘level’ in function metabin etc. is not
equal to the default 0.95. (this bug has been introduced in version
3.0-0 of meta)
Functions metabin, metacont, metacor, metagen, metainc,
metaprop:
- heterogeneity statistics I-squared and H added to R object
- column names changed in list object data (columns starting with a
“.” are used internally in update.meta function)
- internally, string “byvar” is used as default label for grouping
variable if argument bylab is not provided.
Function metareg:
- internally variable .byvar used instead of byvar to reflect change
in list object data (see above)
Function update.meta:
- arguments ‘byvar’ and ‘subset’ fully functional
- internally variables .TE (etc) used instead of TE (etc) to reflect
change in list object data (see above)
Functions trimfill.default and trimfill.meta:
- heterogeneity statistics I-squared and H added to R object
Function metagen:
- bug fix such that weights (w.fixed, w.random) are calculated
correctly if any standard error is missing or zero for Hartung-Knapp
method (argument hakn=TRUE) or not using the DerSimonian Laird method
(argument method.tau not equal to “DL”)
Function summary.meta:
- implement subgroup analysis for metainc objects
- only (re)calculate heterogeneity statistics (Q, tau-squared,
I-squared) for R objects generated with older versions of R package
meta
Function forest.meta:
- groups will not be sorted automatically in alphabetical order (new
argument ‘bysort’). Use argument bysort=FALSE, in order to get the old
behaviour of forest.meta function.
- only (re)calculate heterogeneity statistics (Q, tau-squared,
I-squared) for R objects generated with older versions of R package
meta
Function catmeth (used internally)
- new argument ‘tau.preset’ to print information if between-study
variance was pre-specified
Function print.meta and print.summary.meta
- argument ‘tau.preset’ used in call to function catmeth
New internally used functions isquared and calcH
Some help pages updated
- Function forest.meta:
- bug fix such that forest plot with subgroups will not result in an
error for any meta-analysis object besides metaprop objects (this bug
has been introduced in version 3.1-1 of meta)
- Function forest.meta:
- bug fix such that random effects estimate will be printed for
subgroups for metaprop objects using summary measure “PFT”
New R function metainc (meta-analysis of incidence
rates)
Continuity correction:
- R functions 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
Functions forest.meta, funnel.default, funnel.meta, print.meta,
print.summary.meta, update.meta, catmeth, xlab:
- modified to properly handle R objects of class “metainc”
Function metaprop:
- use correct variable names for ‘event’ and ‘n’ in list object data
if R function metaprop is called without argument data
Function metabin:
- inverse variance method (argument sm=“Inverse”) is used
automatically if argument tau.common is TRUE
- bug fix such that call of R function metabin will not result in an
error if argument tau.common is TRUE and method is equal to “MH”
(Mantel-Haenszel method)
Function catmeth (used internally in R function
print.summmary.meta):
- print information on continuity correction for objects of class
metabin, metaprop, and metainc
Function summary.meta:
- modified such that fixed effect and random effects estimates and
confidence intervals are only (re)calculated for very old versions of R
package meta (version number < 2.x-x) if argument
level.comb has not been used
Functions trimfill.meta and trimfill.default:
- new list components lower.fixed, upper.fixed, zval.fixed,
pval.fixed, lower.random, upper.random, zval.random, pval.random added
to trimfill R object (should/could have been part of exported list since
meta, version 2.0-0)
New datasets smoking and lungcancer (example datasets for R
function metainc)
Major revision
This update has been declared as major revision as the user interface
has been changed by dropping arguments for the following functions: -
print.meta (arguments level, level.comb, level.prediction removed) -
summary.meta (byvar, level, level.comb, level.prediction) - metainf
(level.comb) - metacum (level.comb) - forest.meta (byvar, level,
level.comb, level.predict) This functionality is now provided by R
function update.meta - see help page of R function update.meta for
further details.
Details
New function update.meta
- update an existing meta-analysis object which was created with R
function metabin, metacont, metagen, metaprop, or metacor
New function cilayout
- change layout to print confidence intervals (in printout from R
functions print.meta, print.summary.meta, and forest.meta)
Deprecated function plot.meta removed
Functions metabin, metacont, metagen, metaprop, metacor:
- code cleaning (in preparation for R function update.meta)
- new list components:
- data (original data(set) used in function call)
- subset (information on subset of original data used in
meta-analysis)
Function summary.meta:
- new list components:
- data (original data(set) used in function call)
- subset (information on subset of original data used in
meta-analysis)
Functions metareg:
- argument ‘data’ renamed to ‘x’
- first two arguments interchanged (which is now in line with other R
functions from R package meta)
- modified such that information on grouping variable (list element
‘byvar’) is utilised if argument ‘formula’ is missing
- any column from original dataset (list component ‘data’ in metabin
object (etc) can be used in meta-regression
Function trimfill.meta:
- new defaults for arguments ‘comb.fixed’ and ‘comb.random’ (by
default only random effects estimate calculated)
- arguments ‘sm’ and ‘studlab’ removed (values have been overwritten
internally anyway)
- new list components (depending on class of meta-analysis object used
in function call):
- event.e, event.c, event (number of events)
- n.e, n.c, n (number of observations)
- mean.e, mean.c, sd.e, sd.c (Mean and standard deviation)
- cor (correlation)
- class.x (class of meta object used in function call)
Function trimfill.default:
- new default for argument comb.fixed (by default only random effects
estimate calculated)
Function metacr:
- new list components for Peto O-E method:
- event.e, n.e, event.c, n.c
Function metaprop:
- new list component incr.event
Function forest.meta:
- bug fix such that call of forest.meta function will not result in an
error in the following setting: (i) effect measure is equal to RR, OR,
or HR and (ii) argument label is not a logical value.
Function print.summary.meta:
- modified such that “0” instead of “< 0.0001” is printed if
between-study heterogeneity tau-squared is equal to 0
New function format.tau (used internally):
- print “0” instead of “< 0.0001” if tau-squared is zero
Function p.ci (used internally):
- new arguments bracket.left, separator, bracket.right for more
flexible layouts to print confidence intervals (see also R function
cilayout)
Several help pages updated.
- Function forest.meta:
- new argument just.studlab to change justification of study
labels
- Function print.meta:
- print correct information on method to calculate approximate
confidence interval for ‘metaprop’ objects with a single study
- Function trimfill.meta:
- new list components title, complab, outclab, label.e, label.c,
label.left, label.right which are utilised in other R functions to
enhance printout (see information on version 2.0-0 of R package
meta)
- Function metacr:
- new arguments prediction and level.predict (prediction interval for
a new study)
- new argument tau.common (common tau-squared across subgroups)
- new arguments level and level.comb (confidence interval for single
study / meta-analysis)
- Functions trimfill.meta and trimfill.default:
- new arguments prediction and level.predict (prediction interval for
a new study)
- Function forest.meta:
- modified such that heterogeneity statistics are only printed in
forest plot if results for fixed effect and/or random effects model are
plotted (new defaults for arguments print.I2, print.tau2, and
print.pval.Q)
- Functions metagen, metabin, metacont, metaprop, metacor:
- modified such that list components comb.fixed, comb.random, and
prediction are set to FALSE for a single study (no meta-analysis for a
single study)
- Functions print.meta, print.summary.meta:
- new argument logscale which can be used to print results for summary
measures ‘RR’, ‘OR’, ‘HR’, or ‘PLN’ on logarithmic scale
- Several help pages updated
- Function metaprop:
- bug fix such that call of forest.meta function with metaprop object
does not result in an error (bug was introduced in version 2.4-0 of
meta)
- new list components incr, allincr, addincr added to metaprop R
object (should have been part of exported list since
meta, version 1.5-0)
- Function print.meta:
- new arguments prediction and level.predict to print prediction
interval for a new study
- Function print.summary.meta:
- call of internal function asin2p using argument warn to only print
warnings if result for fixed effect, random effects model or prediction
interval are printed
- Function forest.meta:
- call of internal function asin2p using argument warn to only print
warnings if result for fixed effect, random effects model or prediction
interval are plotted
- Function asin2p (used internally for metaprop objects):
- new argument warn to only print a warning in certain situations (see
comments on functions print.meta and forest.meta)
- Help pages metabin, metacont, metacor, metacr, metagen, metaprop:
- example to generate forest plot added
- Functions metagen, metabin, metacont, metaprop, metacor:
- new arguments prediction and level.predict (prediction interval for
a new study)
- new argument tau.common (common tau-squared across subgroups)
- help pages updated accordingly
- Function metaprop:
- new default summary measure (sm=“PLOGIT”)
- argument freeman.tukey removed
- Function summary.meta:
- new arguments prediction and level.predict (prediction interval for
a new study)
- new list component tau.common considered internally (for objects of
type metagen, metabin, metacont, metaprop, metacor)
- modified such that correct values for list components incr, allincr,
and addincr of metaprop object are considered in calculations
- Function forest.meta:
- modified such that prediction interval can be plotted (new
arguments: prediction, level.predict, text.predict, col.predict,
col.predict.lines, fs.predict, fs.predict.labels, ff.predict,
ff.predict.labels)
- modified such that correct values for list components incr, allincr,
and addincr of metaprop object are considered in calculations
- modified such that information on confidence limits is printed for
pooled estimates if CI level is different from CI level for individual
studies
- Function print.summary.meta:
- modified such that a prediction interval is printed if argument
prediction is TRUE
- new list component tau.common considered internally (for objects of
type metagen, metabin, metacont, metaprop, metacor)
- Function catmeth (only used internally):
- print information if common tau-squared assumed across subgroups
(argument tau.common)
- Function forest.meta:
- modified such that fixed effect and random effects estimates and
confidence intervals are only (re)calculated for very old versions of R
package meta (version number < 2.x-x)
- Functions metabin:
- bug fix such that function call with arguments sm=“RR” and
allstudies=TRUE does not result in an error in meta-analyses with zero
events in both groups
- Function forest.meta:
- new argument lab.NA (default: lab.NA=“.”) to label NAs (in older
version of R package meta the fixed label ‘NA’ was
used)
- modified such that arguments colgap.forest.left and
colgap.forest.right are considered (instead of only colgap.forest)
- Functions labbe.metabin and labbe.default:
- bug fix such that function call does not result in an error if any
event probability is equal to NA
- Function format.p (only used internally):
- bug fix such that function call does not result in an error if any
NAs were provided in the first function argument
- Function metabin:
- modified so that studies with all events in both groups will be
included in meta-analysis by default (in older versions of R package
meta these studies were only included if argument
allstudies=TRUE)
- modified so that the standard error is positive for studies with all
events in both groups (see Hartung & Knapp (2001), Stat Med,
equation (18))
- Function forest.meta:
- modified so that values provided by argument xlim will be printed on
x-axis label for relative effect measures (i.e. argument sm is equal to
“RR”, “OR”, or “HR”)
- internally calculated default values for arguments smlab.pos and
xlab.pos changed such that they will always lie within plotting
range
- Functions forest.meta, metacum, metainf and print.meta:
- modified so that backtransformation of Freeman-Tukey Double arcsine
transformation (argument sm=‘PFT’ in function metaprop) is calculated
correctly for objects of class ‘metacum’ and ‘metainf’
- Function asin2p:
- modified so that values outside the admissible range are set to the
boundary values (i.e. results in estimated probabilities of 0 or 1). A
warning is printed in this case.
- Help pages metacum and metainf:
- new argument n.harmonic.mean documented
- Function forest.meta:
- modified so that the function works for an object of class ‘metacum’
or ‘metainf’ and argument sm equal to ‘PFT’ which previously resulted in
an error message ‘Error in if (col\(range[1]
<= TE.fixed & TE.fixed <= col\)range[2]) …’
- Functions forest.meta, metacum, metainf, summary.meta:
- modified so that the function works if argument ‘method.tau’ is
different from the default which previously resulted in an error message
’Error in sqrt(W) %*% X : non-conformable arguments’
- Function forest.meta:
- argument ‘byvar’ uses corresponding list element from meta-analysis
object as default
- Function summary.meta:
- list element ‘k0’ added to returned object for trim-and-fill
method
- Function print.summary.meta:
- print number of added studies for trim-and-fill method
- Functions trimfill.meta and trimfill.default:
- arguments hakn and method.tau added
- Functions metacum and metainf:
- modified so that class ‘trimfill’ is added to object if function
metacum or metainf is used on object of class ‘trimfill’
- Function catmeth, print.meta, print.summary.meta:
- modified so that information on use of trim-and-fill method is
printed
- Functions metabias.meta:
- modified so that an error message is printed if used with object of
class ‘metacum’ or ‘metainf’
- Functions funnel.meta:
- modified so that an error message is printed if used with object of
class ‘metacum’ or ‘metainf’
- modified so that by default different plot symbols (argument pch)
are used with object of class ‘trimfill’
- Function .onLoad:
- modified so that version nummer of meta package is
printed when library is loaded
- Help pages trimfill.meta and trimfill.default:
- arguments hakn and method.tau documented
- Help page funnel.meta:
- changed default for argument pch documented
- Function metaprop:
- modified so that variance estimate for log- and logit-transformation
(sm=“PLN” and sm=“PLOGIT”) is based on Pettigrew et al. (1986).
- Reference Pettigrew et al. (1986) has been added to the following
help pages:
- Function metaprop:
- modified so that a warning is printed if any sample size
(argument
- is smaller than 10 for Freeman-Tukey double arcsine transformation,
i.e. sm=“PFT”
- Functions metabin, metacont, metacor, metagen, metaprop:
- modified so that these functions can be used with arguments subset
and byvar of different length
Major revision
R package meta linked to R package
metafor to provide additional statistical methods,
e.g. meta-regression and other estimates for tau-squared (REML, …)
Details
New functions:
- metareg (meta-regression)
- metabias (generic method for function metabias)
- metabias.default (generic method for function metabias)
- metabias.meta (generic method for function metabias)
- metabias.rm5 (generic method for function metabias)
- print.rm5 (generic method for rm5-object)
- print.summary.rm5 (generic method for rm5-object)
- summary.rm5 (generic method for rm5-object)
- catmeth (function used internally)
- crtitle (function used internally)
- hypergeometric (function used internally)
- is.installed.metafor (function used internally)
- kentau (function used internally)
- linregcore (function used internally)
- p2logit (function used internally)
Functions metabin, metacont, metacor, metagen, metaprop:
- new arguments:
- hakn (Hartung-Knapp method)
- method.tau (estimation method for tau-squared)
- 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)
- label.left (Label on left side of forest plot, new argument in
functions metabin, metacont, and metagen)
- label.right (Label on right side of forest plot, new argument in
functions metabin, metacont, and metagen)
- warn (print warning messages, new argument in functions metacont and
metagen)
- new list components of returned object:
- se.tau2 (standard error of tau-squared)
- hakn (Hartung-Knapp method)
- method.tau (estimation method for tau-squared)
- 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)
- label.left (Label on left side of forst plot, new list component in
functions metabin, metacont, and metagen)
- label.right (Label on right side of forst plot, new list component
in functions metabin, metacont, and metagen)
- argument ‘warn’ suppresses more warning messages if FALSE
- function 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)
Function metacum and metainf:
- modified so that NULL is returned if function is used with a single
study
- modified so that new arguments hakn, method.tau, tau.preset,
method.bias, label.left, label.right are considered in execution of the
function
- argument level removed
Function metaprop:
- modified so that the correct variance function 1/(n+0.5) instead of
1/(n+1) is used for the Freeman-Tukey double arcsine transformation
(i.e. sm=“PFT”) - see also news on function asin2p
Function 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 R command metaprop
Function print.metabias:
- print a warning if number of studies is too small to conduct a test
for funnel plot asymmetry (see new argument k.min)
Function print.summary.meta:
- new argument bylab.nchar
- print test for subgroup differences for both fixed effect and random
effects model
- value ‘invisible(NULL)’ returned for metacum and metainf
objects
Function 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)
- value ‘NULL’ returned if no data is available for selection of
comp.no and outcome.no
Function read.rm5:
- changed substantially for reading of RevMan 5.1 files
Function summary.meta:
- modified so that new arguments hakn, method.tau, tau.preset,
method.bias are considered in execution of the function
- argument ‘warn’ suppresses more warning messages
Function forest.meta:
- modified so that the 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 (Label for summary measure - at
top of figure)
- label.right, label.left, fs.lr, ff.lr (Label on right and left
side)
- overall.hetstat (heterogeneity information for overall effect)
Function funnel.default and funnel.meta:
- modified so that arguments col.fixed and col.random are
recognised
Function metabias.default and metabias.meta:
- new argument k.min: test for funnel plot asymmetry only conducted if
number of studies in meta-analysis is larger or equal to k.min
- new argument ‘…’ (ignored at the moment)
Function trimfill.default and trimfill.meta:
- value ‘invisible(NULL)’ returned 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
- Function forest.meta:
- modified so that the number of events is printed in the correct
order for objects of class metaprop if argument sort or order is
used
- modified so that transformed proportions are printed for individual
studies in column ‘TE’ if function metagen is used with argument sm
equal to either ‘PLN’, ‘PLOGIT’, ‘PAS’, or ‘PFT’
- Function as.data.frame.meta:
- modified so that the function works for meta-analyses with six
studies which previously resulted in an error message ‘Error: evaluation
nested too deeply: infinite recursion …’
- modified so that additional arguments ‘…’ can be passed to
function
- Function addvar:
- option stringsAsFactors=FALSE added to internal call of R function
as.data.frame.meta
- additional checks for existence of columns by.x and by.y
- additional checks for situations with duplicate entries for columns
by.x and by.y added
- Function print.meta:
- modified so that back-transformed proportions are printed for
individual studies if function metagen is used with argument sm equal to
either ‘PLN’, ‘PLOGIT’, ‘PAS’, or ‘PFT’
- Examples in help pages (slightly) updated:
- read.mtv, read.rm5, metacr
- Function forest.meta:
- for subgroup analyses (i.e. groups defined by argument ‘byvar’),
result for both fixed effect and random effects model are printed (in
older versions of the meta package only results for
either fixed effect or random effects model could be printed)
- new arguments text.fixed.w and text.random.w to specify label for
estimates within subgroups
- new arguments to change colour of several parts of the plot:
col.i.inside.square, col.square, col.square.lines, col.diamond,
col.diamond.fixed, col.diamond.random, col.diamond.lines,
col.diamond.fixed.lines, col.diamond.random.lines
- new arguments to print information on heterogeneity measures:
print.I2, print.tau2, print.Q, print.pval.Q, hetstat, hetlab
- new arguments to change fontsize and fontface of several parts of
the plot: fs.heading, fs.fixed, fs.random, fs.study, fs.fixed.labels,
fs.random.labels, fs.study.labels, fs.hetstat, fs.axis, fs.xlab,
ff.heading, ff.fixed, ff.random, ff.study, ff.fixed.labels,
ff.random.labels, ff.study.labels, ff.hetstat, ff.axis, ff.xlab
- new arguments to change gap between columns colgap.left,
colgap.right=colgap, colgap.forest, colgap.forest.left,
colgap.forest.right
- new argument ‘just’ to change justification of text for additional
columns
- new argument ‘addspace’ to print a blank line at top and bottom of
study results
- argument ‘squaresize’ supersedes argument ‘boxsize’
- new argument ‘new’ indicating whether a new figure should be printed
in an existing graphics window (internally, the grid.newpage command is
used if new=TRUE)
- no line is printed for the fixed effect and random effects model if
lty.fixed=NULL or lty.random=NULL, respectively
- symmetric forest plots can be produced by setting argument
xlim=“s”
- Function print.summary.meta:
- new argument print.CMH indicating whether Cochran-Mantel-Haenszel
test for overall effect should be printed (default print.CMH=FALSE)
- For subgroup analyses (i.e. groups defined by argument ‘byvar’),
result for test of heterogeneity printed separately for fixed effect and
random effects model
- Functions metabin and summary.meta:
- new argument print.CMH indicating whether Cochran-Mantel-Haenszel
test for overall effect should be printed (default print.CMH=FALSE)
- Help pages updated:
- forest.meta, metabin, print.summary.meta, summary.meta
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 (function used internally)
- logit2p (function used internally)
- xlab (function used internally)
- z2cor (function used internally)
Functions forest.meta:
- new arguments (pooled.totals, 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
- modified so that argument label is recognised for other effect
measures than RR, OR, and HR
- modified so that argument xlim is recognised for other effect
measures than RR, OR, and HR
- arguments rightlabs and leftlabs accept NAs for columns using
default labels
- modified so that 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
Function 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 (use argument sm
instead)
Functions funnel and funnel.meta:
Functions labbe and labbe.meta:
Functions trimfill and trimfill.meta:
Function summary.meta:
- new list objects H.w, I2.w, Q.b.fixed and Q.b.random for
heterogeneity statistics within subgroups
Extension for meta-analysis of correlations:
- forest.meta, metacum, metainf, print.meta, print.summary.meta,
summary.meta
Function plot.meta:
- a warning is printed that the function is no longer maintained
(function forest.meta should be used instead)
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, metabias).
Several help pages updated
Use file NEWS instead of ChangeLog to document changes
- Functions summary.meta, print.summary.meta:
- modified so that a test for subgroup differences is not calculated
and printed for meta-analyses using the Mantel-Haenszel method for
binary data
- Functions metabin, metacont, metagen, metaprop:
- modified so that a sensible default value is used for argument bylab
if argument byvar is not missing
- Function forest:
- modified so that additional columns are printed in the correct order
if argument sort or order is used
- Function forest (incl. help page):
- new argument digits specifying minimal number of significant digits
for treatment estimate and its confidence interval
- Function summary.meta:
- modified so that results for subgroups (if byvar != NULL) are
calculated for both fixed effect and random effects model:
- list ‘within’ no longer returned by function summary.meta
- lists ‘within.fixed’ and ‘within.random’ returned by function
summary.meta
- modified so that variable name of subgroups is printed
correctly
- check whether input is an object of class summary.meta
- Function print.summary.meta:
- modified so that a warning is printed if both comb.fixed and
comb.random are TRUE and results for subgroups are supposed to be
printed
- Help pages of functions print.summary.meta and forest updated:
- detailed information on printing and plotting of subgroup results if
both comb.fixed and comb.random are TRUE
- Help page of function metagen updated:
- new example with meta-analysis of survival data
- New functions trimfill, trimfill.default and trimfill.meta:
- generic method for trim-and-fill method
- New functions labbe, labbe.default, labbe.metabin:
- New functions funnel, funnel.default and funnel.meta:
- generic method for funnel plots
- Functions funnel.default and funnel.meta:
- modified so that contour-enhanced funnel plots can be produced (new
arguments: contour.levels, col.contour, ref)
- modified so that study labels can be printed on funnel plot (new
arguments: studlab, cex.studlab)
- modified so that line type, width and colour can be changed for
fixed effect treatment effect (new arguments: lty.fixed, lwd.fixed,
col.fixed)
- modified so that random effects treatment effect can be plotted (new
arguments: comb.random, lty.random, lwd.random, col.random)
- new default values for arguments:
- pch=21 (previously: pch=1)
- comb.fixed=x$comb.fixed
- modified so that background colour of points in funnel plot can be
changed (new argument: bg)
- Function forest:
- new default values for arguments lab.e and lab.c: x\(label.e and x\)label.c, respectively. If
these values are NULL the old default values “Experimental” and
“Control” are used.
- Functions metabin, metacont, metagen:
- arguments label.e and label.c added
- Function metacr:
- use arguments label.e and label.c in calls to functions metabin,
metacont, metagen