metaobject  R Documentation 
Detailed description of R objects of class "meta".
The following R functions create an object of class "meta"
:
metabin
, metacont
,
metacor
, metagen
,
metainc
, metamean
,
metaprop
, metarate
,
metacr
, metamerge
,
trimfill
The following generic functions are available for an object of
class "meta"
:
as.data.frame.meta
, labels.meta
,
print.meta
, print.summary.meta
,
summary.meta
, update.meta
,
weights.meta
An object of class "meta"
is a list containing the following
components.
studlab  Study labels 
sm  Effect measure 
null.effect  Effect under the null hypothesis 
TE  Effect estimates (individual studies) 
seTE  Standard error of effect estimates (individual studies) 
statistic  Statistics for test of effect (individual studies) 
pval  Pvalues for test of effect (individual studies) 
df  Degrees of freedom (individual studies) 
level  Level of confidence intervals for individual studies 
lower  Lower confidence limits (individual studies) 
upper  Upper confidence limits (individual studies) 
three.level  Indicator variable for threelevel metaanalysis model 
cluster  Cluster variable (threelevel metaanalysis model) 
k  Number of estimates combined in metaanalysis 
k.study  Number of studies combined in metaanalysis 
k.all  Number of all studies 
k.TE  Number of studies with estimable effects 
overall  Print metaanalysis results 
overall.hetstat  Print overall heterogeneity statistics 
common  Print results for common effect metaanalysis 
random  Print results for random effects metaanalysis 
prediction  Print prediction interval 
backtransf  Back transform results in printouts and plots 
method  Metaanalysis method (common effect model) 
method.random  Metaanalysis method (random effects model) 
w.common  Weights for common effect model (individual studies) 
TE.common  Estimated overall effect (common effect model) 
seTE.common  Standard error of overall effect (common effect model) 
statistic.common  Statistic for test of overall effect (common effect model) 
pval.common  Pvalue for test of overall effect (common effect model) 
level.ma  Level of confidence interval for metaanalysis estimates 
lower.common  Lower confidence limit (common effect model) 
upper.common  Upper confidence limit (common effect model) 
w.random  Weight for random effects model (individual studies) 
TE.random  Estimated overall effect (random effects model) 
seTE.random  Standard error of overall effect (random effects model) 
statistic.random  Statistic for test of overall effect (random effects model) 
pval.random  Pvalue for test of overall effect (random effects model) 
method.random.ci  Confidence interval method (random effects model) 
df.random  Degrees of freedom (random effects model) 
lower.random  Lower confidence limit (random effects model) 
upper.random  Upper confidence limit (random effects model) 
seTE.classic  Standard error (classic random effects method) 
adhoc.hakn.ci  Ad hoc correction for HartungKnapp method (confidence interval) 
df.hakn.ci  Degrees of freedom for HartungKnapp method 
(if used in metaanalysis)  
seTE.hakn.ci  Standard error for HartungKnapp method 
(not taking ad hoc variance correction into account)  
seTE.hakn.adhoc.ci  Standard error for HartungKnapp method 
(taking ad hoc variance correction into account)  
df.kero  Degrees of freedom for KenwardRoger method 
(if used in metaanalysis)  
seTE.kero  Standard error for KenwardRoger method 
method.predict  Method to calculate prediction interval 
adhoc.hakn.pi  Ad hoc correction for HartungKnapp method (prediction interval) 
df.hakn.ci  Degrees of freedom for HartungKnapp method 
(prediction interval)  
seTE.predict  Standard error used to calculate prediction interval 
df.predict  Degrees of freedom for prediction interval 
level.predict  Level of prediction interval 
lower.predict  Lower limit of prediction interval 
upper.predict  Upper limit of prediction interval 
seTE.hakn.pi  Standard error for HartungKnapp method 
(not taking ad hoc variance correction into account)  
seTE.hakn.adhoc.pi  Standard error for HartungKnapp method 
(taking ad hoc variance correction into account)  
Q  Heterogeneity statistic 
df.Q  Degrees of freedom for heterogeneity statistic
Q 
pval.Q  Pvalue of heterogeneity test 
method.tau  Method to estimate betweenstudy variance \tau^2 
control  Additional arguments for iterative estimation
of \tau^2 
method.tau.ci  Method for confidence interval of \tau^2 
tau2  Betweenstudy variance \tau^2 
se.tau2  Standard error of \tau^2 
lower.tau2  Lower confidence limit (\tau^2 ) 
upper.tau2  Upper confidence limit (\tau^2 ) 
tau  Squareroot of betweenstudy variance \tau 
lower.tau  Lower confidence limit (\tau ) 
upper.tau  Upper confidence limit (\tau ) 
tau.preset  Prespecified value for \tau 
TE.tau  Effect estimate used to estimate \tau^2 
detail.tau  Detail on betweenstudy variance estimate 
H  Heterogeneity statistic H 
lower.H  Lower confidence limit (heterogeneity statistic H) 
upper.H  Upper confidence limit (heterogeneity statistic H) 
I2  Heterogeneity statistic I^2 
lower.I2  Lower confidence limit (heterogeneity statistic I^2 ) 
upper.I2  Upper confidence limit (heterogeneity statistic I^2 ) 
Rb  Heterogeneity statistic R_b 
lower.Rb  Lower confidence limit (heterogeneity statistic R_b ) 
upper.Rb  Upper confidence limit (heterogeneity statistic R_b ) 
method.bias  Method to test for funnel plot asymmetry 
text.common  Label for common effect model 
text.random  Label for random effects model 
text.predict  Label for prediction interval 
text.w.common  Label for weights (common effect model) 
text.w.random  Label for weights (random effects model) 
title  Title of metaanalysis / systematic review 
complab  Comparison label 
outclab  Outcome label 
label.e  Label for experimental group 
label.c  Label for control group 
label.left  Graph label on left side of forest plot 
label.right  Graph label on right side of forest plot 
keepdata  Keep original data 
data  Original data (set) used in function call (if
keepdata = TRUE ) 
subset  Information on subset of original data used in metaanalysis 
(if keepdata = TRUE ) 

exclude  Studies excluded from metaanalysis 
warn  Print warnings 
call  Function call 
version  Version of R package meta used to create object 
For subgroup analysis (argument subgroup
), the following
additional components are added to the list.
subgroup  Subgroup information (for individual studies) 
subgroup.name  Name of subgroup variable 
print.subgroup.name  Print name of subgroup variable 
sep.subgroup  Separator between name of subgroup variable and value 
test.subgroup  Print test for subgroup differences 
prediction.subgroup  Print prediction interval for subgroup(s) 
tau.common  Assumption of common betweenstudy variance in subgroups 
subgroup.levels  Levels of grouping variable 
k.w  Number of estimates combined in subgroups 
k.study.w  Number of studies combined in subgroups 
k.all.w  Number of studies in subgroups 
k.TE.w  Number of studies with estimable effects in subgroups 
TE.common.w  Estimated effect in subgroups (common effect model) 
seTE.common.w  Standard error in subgroups (common effect model) 
statistic.common.w  Statistic for test of effect in subgroups (common effect model) 
pval.common.w  Pvalue for test of effect in subgroups (common effect model) 
lower.common.w  Lower confidence limit in subgroups (common effect model) 
upper.common.w  Upper confidence limit in subgroups (common effect model) 
w.common.w  Total weight in subgroups (common effect model) 
TE.random.w  Estimated effect in subgroups (random effect model) 
seTE.random.w  Standard error in subgroups (random effects model) 
statistic.random.w  Statistic for test of effect in subgroups (random effects model) 
pval.random.w  Pvalue for test of effect in subgroups (random effects model) 
df.random.w  Degrees of freedom in subgroups (random effects model) 
lower.random.w  Lower confidence limit in subgroups (random effects model) 
upper.random.w  Upper confidence limit in subgroups (random effects model) 
w.random.w  Total weight in subgroups (random effects model) 
seTE.classic.w  Standard error (classic random effects method) 
df.hakn.ci.w  Degrees of freedom for HartungKnapp method in subgroups 
seTE.hakn.ci.w  Standard error for HartungKnapp method in subgroups 
(not taking ad hoc variance correction into account)  
seTE.hakn.adhoc.ci.w  Standard error for HartungKnapp method in subgroups 
df.kero.w  Degrees of freedom for KenwardRoger method in subgroups 
seTE.kero.w  Standard error for KenwardRoger method in subgroups 
seTE.predict.w  Standard error for prediction interval in subgroups 
df.predict.w  Degrees of freedom for prediction interval in subgroups 
lower.predict.w  Lower limit of prediction interval in subgroups 
upper.predict.w  Upper limit of prediction interval in subgroups 
seTE.hakn.pi.w  Standard error for HartungKnapp method in subgroups (prediction intervals) 
(not taking ad hoc variance correction into account)  
seTE.hakn.adhoc.pi.w  Standard error for HartungKnapp method in subgroups (prediction intervals) 
Q.w  Heterogeneity statistic Q in subgroups 
pval.Q.w  Pvalue for test of heterogeneity in subgroups 
tau2.w  Betweenstudy variance \tau^2 in subgroups 
tau.w  Squareroot of betweenstudy variance \tau in subgroups 
H.w  Heterogeneity statistic H in subgroups 
lower.H.w  Lower confidence limit for H in subgroups 
upper.H.w  Upper confidence limit for H in subgroups 
I2.w  Heterogeneity statistic I^2 in subgroups 
lower.I2.w  Lower confidence limit for I^2 in subgroups 
upper.I2.w  Upper confidence limit for I^2 in subgroups 
Rb.w  Heterogeneity statistic R_b in subgroups 
lower.Rb.w  Lower confidence limit for R_b in subgroups 
upper.Rb.w  Upper confidence limit for R_b in subgroups 
Q.w.common  Withingroup heterogeneity statistic Q (common effect model) 
Q.w.random  Withingroup heterogeneity statistic Q (random effects model) 
(only calculated if argument tau.common = TRUE ) 

df.Q.w  Degrees of freedom for Q.w.common and Q.w.random 
pval.Q.w.common  Pvalue of test for residual heterogeneity (common effect model) 
pval.Q.w.random  Pvalue of test for residual heterogeneity (random effects model) 
Q.b.common  Betweengroups heterogeneity statistic Q (common effect model) 
df.Q.b.common  Degrees of freedom for Q.b.common

pval.Q.b.common  Pvalue of test for subgroup differences (common effect model) 
Q.b.random  Betweengroups heterogeneity statistic Q (random effects model) 
df.Q.b.random  Degrees of freedom for Q.b.random

pval.Q.b.random  Pvalue of test for subgroup differences (random effects model) 
An object created with metabin
has the additional
class "metabin"
and the following components.
event.e  Events in experimental group (individual studies) 
n.e  Sample size in experimental group (individual studies) 
event.e  Events in control group (individual studies) 
n.e  Sample size in control group (individual studies) 
incr  Increment added to zero cells 
method.incr  Continuity correction method 
sparse  Continuity correction applied 
allstudies  Include studies with double zeros 
doublezeros  Indicator for studies with double zeros 
MH.exact  Exact MantelHaenszel method 
RR.Cochrane  Cochrane method to calculate risk ratio 
Q.Cochrane  Cochrane method to calculate \tau^2

Q.CMH  CochranMantelHaenszel statistic 
df.Q.CMH  Degrees of freedom for Q.CMH 
pval.Q.CMH  Pvalue of CochranMantelHaenszel test 
print.CMH  Print results for CochranMantelHaenszel statistic 
incr.e  Continuity correction in experimental group (individual studies) 
incr.c  Continuity correction in control group (individual studies) 
k.MH  Number of studies (MantelHaenszel method) 
An object created with metacont
has the additional
class "metacont"
and the following components.
n.e  Sample size in experimental group (individual studies) 
mean.e  Estimated mean in experimental group (individual studies) 
sd.e  Standard deviation in experimental group (individual studies) 
n.c  Sample size in control group (individual studies) 
mean.c  Estimated mean in control group (individual studies) 
sd.c  Standard deviation in control group (individual studies) 
pooledvar  Use pooled variance for mean difference 
method.smd  Method for standardised mean difference (SMD) 
sd.glass  Denominator in Glass' method 
exact.smd  Use exact formulae for SMD 
method.ci  Method to calculate confidence limits 
method.mean  Method to approximate mean 
method.sd  Method to approximate standard deviation 
An object created with metacor
has the additional
class "metacor"
and the following components.
cor  Correlation (individual studies) 
n  Sample size (individual studies) 
An object created with metainc
has the additional
class "metainc"
and the following components.
event.e  Events in experimental group (individual studies) 
time.e  Person time in experimental group (individual studies) 
n.e  Sample size in experimental group (individual studies) 
event.c  Events in control group (individual studies) 
time.c  Person time in control group (individual studies) 
n.c  Sample size in control group (individual studies) 
incr  Increment added to zero cells 
method.incr  Continuity correction method 
sparse  Continuity correction applied 
incr.event  Continuity correction (individual studies) 
k.MH  Number of studies (MantelHaenszel method) 
An object created with metamean
has the additional
class "metamean"
and the following components.
n  Sample size (individual studies) 
mean  Estimated mean (individual studies) 
sd  Standard deviation (individual studies) 
method.ci  Method to calculate confidence limits 
method.mean  Method to approximate mean 
method.sd  Method to approximate standard deviation 
An object created with metaprop
has the additional
class "metaprop"
and the following components.
event  Events (individual studies) 
n  Sample size (individual studies) 
incr  Increment added to zero cells 
method.incr  Continuity correction method 
sparse  Continuity correction applied 
method.ci  Method to calculate confidence limits 
incr.event  Continuity correction (individual studies) 
An object created with metarate
has the additional
class "metarate"
and the following components.
event  Events (individual studies) 
time  Person time (individual studies) 
n  Sample size (individual studies) 
incr  Increment added to zero cells 
method.incr  Continuity correction method 
sparse  Continuity correction applied 
method.ci  Method to calculate confidence limits 
incr.event  Continuity correction (individual studies) 
An object created with trimfill
has the additional
classes "trimfill"
and "metagen"
and the following
components.
k0  Number of added studies 
left  Studies missing on left side 
ma.common  Use common effect or random effects model to estimate 
number of missing studies  
type  Method to estimate missing studies 
n.iter.max  Maximum number of iterations 
n.iter  Number of iterations 
trimfill  Filled studies (individual studies) 
class.x  Primary class of metaanalysis object 
An object created with metamerge
has the additional
class "metamerge"
. Furthermore, the following components
have a different meaning:
k  Vector with number of estimates 
k.study  Vector with number of studies 
k.all  Vector with total number of studies 
k.TE  Vector with number of studies with estimable effects 
k.MH  Vector with number of studies combined with MantelHaenszel method 
TE.common  Vector with common effect estimates 
seTE.common  Vector with standard errors of common effect estimates 
lower.common  Vector with lower confidence limits (common effect model) 
upper.common  Vector with upper confidence limits (common effect model) 
statistic.common  Vector with test statistics for test of overall effect (common effect model) 
pval.common  Vector with pvalue of test for overall effect (common effect model) 
TE.random  Vector with random effects estimates 
seTE.random  Vector with standard errors of random effects estimates 
lower.random  Vector with lower confidence limits (random effects model) 
upper.random  Vector with upper confidence limits (random effects model) 
statistic.random  Vector with test statistics for test of overall effect (random effects model) 
pval.random  Vector with pvalue of test for overall effect (random effects model) 
w.common  Vector or matrix with common effect weights 
w.random  Vector or matrix with random effects weights 
Guido Schwarzer guido.schwarzer@uniklinikfreiburg.de
metapackage
, metasm
,
print.meta
, summary.meta
,
forest.meta
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.