print.meta {meta}R Documentation

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, level=x$level, level.comb=x$level.comb,
      details=FALSE, ma=TRUE, digits=max(4, .Options$digits - 3), ...)

## S3 method for class 'meta':
summary(object, byvar, bylab, bystud=FALSE,
        level=object$level, level.comb=object$level.comb, warn=TRUE, ...)

## S3 method for class 'summary.meta':
print(x, digits = max(3, .Options$digits - 3),
      print.byvar = TRUE, ...)

Arguments

x An object of class meta 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$TE).
level The level used to calculate confidence intervals for individual studies.
level.comb The level used to calculate confidence intervals for pooled estimates.
details A logical indicating whether further details of individual studies should be printed.
ma A logical indicating whether the summary results of the meta-analysis should be printed.
byvar An optional vector containing grouping information (must be of same length as x$TE).
bylab A character string with a label for the grouping variable.
bystud A logical indicating whether results of individual studies should be printed by grouping variable.
digits Minimal number of significant digits, see print.default.
print.byvar A logical indicating whether the name of the grouping variable should be printed in front of the group labels.
warn A logical indicating whether the use of summary.meta in connection with metacum or metainf should result in a warning.
... other arguments

Value

A list is returned by the function summary.meta with the following elements:

study Results for individual studies (a list with elements TE, seTE, lower, upper, z, p, level).
fixed Results for fixed effect model (a list with elements TE, seTE, lower, upper, z, p, level).
random Results for random effects model (a list with elements TE, seTE, lower, upper, z, p, level).
k Number of studies combined in meta-analysis.
Q Heterogeneity statistic Q.
tau Square-root of between-study variance (moment estimator of DerSimonian-Laird).
H Heterogeneity statistic H (a list with elements TE, lower, upper).
I2 Heterogeneity statistic I2 (a list with elements TE, lower, upper), see Higgins & Thompson (2002).
k.all Total number of trials.
Q.CMH Cochrane-Mantel-Haenszel heterogeneity statistic.
sm A character string indicating underlying summary measure.
method A character string with the pooling method.
call Function call.
ci.lab Label for confidence interval.
within Results within groups (a list with elements TE, seTE, lower, upper, z, p, level) - if byvar is not missing.
k.w Number of studies combined within groups - if byvar is not missing.
Q.w Heterogeneity statistic Q within groups - if byvar is not missing.
bylab Label for grouping variable - if byvar is not missing.
by.levs Levels of grouping variable - if byvar is not missing.

Author(s)

Guido Schwarzer sc@imbi.uni-freiburg.de

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

metabin, metacont, metagen

Examples

data(Fleiss93cont)
meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, data=Fleiss93cont, sm="SMD")
summary(meta1)
summary(meta1, byvar=c(1,2,1,1,2), bylab="group")

[Package meta version 0.9-18 Index]