Detailed description of R objects of class "meta".
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
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 | P-values 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 three-level meta-analysis model |
cluster | Cluster variable (three-level meta-analysis model) |
rho | Within-cluster correlation (three-level meta-analysis model) |
k | Number of estimates combined in meta-analysis |
k.study | Number of studies combined in meta-analysis |
k.all | Number of all studies |
k.TE | Number of studies with estimable effects |
overall | Print meta-analysis results |
overall.hetstat | Print overall heterogeneity statistics |
common | Print results for common effect meta-analysis |
random | Print results for random effects meta-analysis |
prediction | Print prediction interval |
backtransf | Back transform results in printouts and plots |
method | Meta-analysis method (common effect model) |
method.random | Meta-analysis 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 | P-value for test of overall effect (common effect model) |
level.ma | Level of confidence interval for meta-analysis 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 | P-value 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 Hartung-Knapp method (confidence interval) |
df.hakn.ci | Degrees of freedom for Hartung-Knapp method |
| (if used in meta-analysis) | |
seTE.hakn.ci | Standard error for Hartung-Knapp method |
| (not taking ad hoc variance correction into account) | |
seTE.hakn.adhoc.ci | Standard error for Hartung-Knapp method |
| (taking ad hoc variance correction into account) | |
df.kero | Degrees of freedom for Kenward-Roger method |
| (if used in meta-analysis) | |
seTE.kero | Standard error for Kenward-Roger method |
method.predict | Method to calculate prediction interval |
adhoc.hakn.pi | Ad hoc correction for Hartung-Knapp method (prediction interval) |
df.hakn.ci | Degrees of freedom for Hartung-Knapp 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 Hartung-Knapp method |
| (not taking ad hoc variance correction into account) | |
seTE.hakn.adhoc.pi | Standard error for Hartung-Knapp method |
| (taking ad hoc variance correction into account) | |
Q | Heterogeneity statistic |
df.Q | Degrees of freedom for heterogeneity statistic
Q |
pval.Q | P-value of heterogeneity test |
method.tau | Method to estimate between-study variance \(\tau^2\) |
control | Additional arguments for iterative estimation of \(\tau^2\) |
method.tau.ci | Method for confidence interval of \(\tau^2\) |
level.hetstat | Level of confidence intervals for heterogeneity statistics |
tau2 | Between-study 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 | Square-root of between-study 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 between-study variance estimate |
phi | Multiplicative heterogeneity parameter \(phi\) in penalised logistic regression |
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 meta-analysis / 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 meta-analysis |
(if keepdata = TRUE) | |
exclude | Studies excluded from meta-analysis |
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 between-study 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 | P-value 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 | P-value 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 Hartung-Knapp method in subgroups |
seTE.hakn.ci.w | Standard error for Hartung-Knapp method in subgroups |
| (not taking ad hoc variance correction into account) | |
seTE.hakn.adhoc.ci.w | Standard error for Hartung-Knapp method in subgroups |
df.kero.w | Degrees of freedom for Kenward-Roger method in subgroups |
seTE.kero.w | Standard error for Kenward-Roger 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 Hartung-Knapp method in subgroups (prediction intervals) |
| (not taking ad hoc variance correction into account) | |
seTE.hakn.adhoc.pi.w | Standard error for Hartung-Knapp method in subgroups (prediction intervals) |
Q.w | Heterogeneity statistic Q in subgroups |
pval.Q.w | P-value for test of heterogeneity in subgroups |
tau2.w | Between-study variance \(\tau^2\) in subgroups |
tau.w | Square-root of between-study 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 | Within-group heterogeneity statistic Q (common effect model) |
Q.w.random | Within-group 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 | P-value of test for residual heterogeneity (common effect model) |
pval.Q.w.random | P-value of test for residual heterogeneity (random effects model) |
Q.b.common | Between-groups heterogeneity statistic Q (common effect model) |
df.Q.b.common | Degrees of freedom for Q.b.common |
pval.Q.b.common | P-value of test for subgroup differences (common effect model) |
Q.b.random | Between-groups heterogeneity statistic Q (random effects model) |
df.Q.b.random | Degrees of freedom for Q.b.random |
pval.Q.b.random | P-value 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 Mantel-Haenszel method |
RR.Cochrane | Cochrane method to calculate risk ratio |
Q.Cochrane | Cochrane method to calculate \(\tau^2\) |
Q.CMH | Cochran-Mantel-Haenszel statistic |
df.Q.CMH | Degrees of freedom for Q.CMH |
pval.Q.CMH | P-value of Cochran-Mantel-Haenszel test |
print.CMH | Print results for Cochran-Mantel-Haenszel statistic |
incr.e | Continuity correction in experimental group (individual studies) |
incr.c | Continuity correction in control group (individual studies) |
k.MH | Number of studies (Mantel-Haenszel 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 (Mantel-Haenszel 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 meta-analysis 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 Mantel-Haenszel 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 p-value 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 p-value 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 |
meta-package, meta-sm,
print.meta, summary.meta,
forest.meta