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meta (version 3.8-0)

print.meta: Print and summary method for objects of class meta

Description

Print and summary method for objects of class meta.

Usage

## S3 method for class 'meta':
print(x, sortvar,
        comb.fixed=x$comb.fixed,
        comb.random=x$comb.random,
        prediction=x$prediction,
        details=FALSE, ma=TRUE, backtransf=x$backtransf,
        digits=max(4, .Options$digits - 3), ...)
## S3 method for class 'metabias':
print(x, ...)
## S3 method for class 'meta':
summary(object,
        comb.fixed=object$comb.fixed, comb.random=object$comb.random,
        prediction=object$prediction,
        backtransf=object$backtransf,
        bylab=object$bylab, print.byvar=object$print.byvar,
        bystud=FALSE, print.CMH=object$print.CMH,
        warn=object$warn, ...)
## S3 method for class 'summary.meta':
print(x, digits = max(3, .Options$digits - 3),
        comb.fixed=x$comb.fixed, comb.random=x$comb.random,
        prediction=x$prediction,
        print.byvar=x$print.byvar, print.CMH=x$print.CMH,
        header=TRUE, backtransf=x$backtransf,
        bylab.nchar=35, ...)
cilayout(bracket="[", separator="; ")

Arguments

x
An object of class meta, metabias, or summary.meta.
object
An object of class meta.
sortvar
An optional vector used to sort the individual studies (must be of same length as x$TE).
comb.fixed
A logical indicating whether a fixed effect meta-analysis should be conducted.
comb.random
A logical indicating whether a random effects meta-analysis should be conducted.
prediction
A logical indicating whether a prediction interval should be printed.
bylab
A character string with a label for the grouping variable.
print.byvar
A logical indicating whether the name of the grouping variable should be printed in front of the group labels.
header
A logical indicating whether information on title of meta-analysis, comparison and outcome should be printed at the beginning of the printout.
details
A logical indicating whether further details of individual studies should be printed.
ma
A logical indicating whether the summary results of the meta-analysis should be printed.
backtransf
A logical indicating whether printed results should be back transformed. If backtransf=TRUE, results for sm="OR" are printed as odds ratios rather than log odds ratios and results for sm="ZCOR" are printe
bylab.nchar
A numeric specifying the number of characters to print from label for the grouping variable.
bystud
A logical indicating whether results of individual studies should be printed by grouping variable.
print.CMH
A logical indicating whether result of the Cochran-Mantel-Haenszel test for overall effect should be printed.
digits
Minimal number of significant digits, see print.default.
warn
A logical indicating whether the use of summary.meta in connection with metacum or metainf should result in a warning.
bracket
A character with bracket symbol to print lower confidence interval: "[", "(", "{", "".
separator
A character string with information on separator between lower and upper confidence interval.
...
Additional arguments.

Value

  • A list is returned by the function summary.meta with the following elements:
  • studyResults for individual studies (a list with elements TE, seTE, lower, upper, z, p, level, df).
  • fixedResults for fixed effect model (a list with elements TE, seTE, lower, upper, z, p, level, df).
  • randomResults for random effects model (a list with elements TE, seTE, lower, upper, z, p, level, df).
  • kNumber of studies combined in meta-analysis.
  • QHeterogeneity statistic Q.
  • tauSquare-root of between-study variance.
  • se.tauStandard error of square-root of between-study variance.
  • CScaling factor utilised internally to calculate common tau-squared across subgroups.
  • HHeterogeneity statistic H (a list with elements TE, lower, upper).
  • I2Heterogeneity statistic I2 (a list with elements TE, lower, upper), see Higgins & Thompson (2002).
  • k.allTotal number of studies.
  • Q.CMHCochran-Mantel-Haenszel test statistic for overall effect.
  • smA character string indicating underlying summary measure.
  • methodA character string with the pooling method.
  • callFunction call.
  • ci.labLabel for confidence interval.
  • haknA logical indicating whether method by Hartung and Knapp was used.
  • method.tauA character string indicating which method is used to estimate the between-study variance tau-squared.
  • tau.commonA logical indicating whether tau-squared is assumed to be the same across subgroups.
  • within.fixedResult for fixed effect model within groups (a list with elements TE, seTE, lower, upper, z, p, level, df, harmonic.mean) - if byvar is not missing.
  • within.randomResult for random effects model within groups (a list with elements TE, seTE, lower, upper, z, p, level, df, harmonic.mean) - if byvar is not missing.
  • k.wNumber of studies combined within groups - if byvar is not missing.
  • Q.wHeterogeneity statistic Q within groups - if byvar is not missing.
  • Q.b.fixedHeterogeneity statistic Q between groups (based on fixed effect model) - if byvar is not missing.
  • Q.b.randomHeterogeneity statistic Q between groups (based on random effects model) - if byvar is not missing.
  • tau.wSquare-root of between-study variance within subgroups - if byvar is not missing.
  • C.wScaling factor utilised internally to calculate common tau-squared across subgroups.
  • H.wHeterogeneity statistic H within subgroups (a list with elements TE, lower, upper) - if byvar is not missing.
  • I2.wHeterogeneity statistic I2 within subgroups (a list with elements TE, lower, upper) - if byvar is not missing.
  • by.levsLevels of grouping variable - if byvar is not missing.
  • titleTitle of meta-analysis / systematic review.
  • complabComparison label.
  • outclabOutcome label.
  • dataOriginal data (set) used to create meta object.
  • subsetInformation on subset of original data used in meta-analysis.
  • prediction, level.predict
  • comb.fixed, comb.random, print.CMHAs defined above.
  • versionVersion of R package meta used to create object.

Details

Note, in R package meta, version 3.0-0 some arguments have been removed from R functions summary.meta (arguments: byvar, level, level.comb, level.prediction) and print.summary.meta (arguments: level, level.comb, level.prediction). This functionality is now provided by R function update.meta (or directly in R functions metabin, metacont, metagen, metacor, and metaprop).

Review Manager 5 (RevMan 5) is the current software used for preparing and maintaining Cochrane Reviews (http://www.cc-ims.net/revman/). In RevMan 5, subgroup analyses can be defined and data from a Cochrane review can be imported to R using the function read.rm5. If a meta-analysis is then conducted using function metacr, information on subgroups is available in R (components byvar, bylab, and print.byvar, byvar in an object of class "meta"). Accordingly, by using function metacr there is no need to define subgroups in order to redo the statistical analysis conducted in the Cochrane review. Note, for an object of type metaprop, starting with version 3.7-0 of meta, list elements TE, lower and upper in element study correspond to transformed proportions and confidence limits (regardless whether exact confidence limits are calculated; argument ciexact=TRUE in metaprop function). Accordingly, the following results are based on the same transformation defined by argument sm: list elements TE, lower and upper in elements study, fixed, random, within.fixed and within.random.

R function cilayout can be utilised to change the layout to print confidence intervals (both in printout from print.meta and print.summary.meta function as well as in forest plots). The default layout is "[lower; upper]". Another popular layout is "(lower - upper)" which is used throughout an R session by using R command cilayout("(", "- ").

References

Cooper H & Hedges LV (1994), The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation.

Higgins JPT & Thompson SG (2002), Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539--1558.

See Also

update.meta, metabin, metacont, metagen

Examples

Run this code
data(Fleiss93cont)
meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, data=Fleiss93cont, sm="SMD")
summary(meta1)

summary(update(meta1, byvar=c(1,2,1,1,2), bylab="group"))

forest(update(meta1, byvar=c(1,2,1,1,2), bylab="group"))

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