meta (version 0.81)

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, level=0.95, level.comb=level,
      details=FALSE, ma=TRUE, digits=max(0, .Options$digits - 3), ...)
## S3 method for class 'meta':
summary(object, byvar, bylab, bystud=FALSE, level.comb=0.95, ...)
## S3 method for class 'summary.meta':
print(x, digits = max(0, .Options$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.

...

other arguments

Value

• A list is returned by the function summary.meta with the following elements:
• 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).
• random
  A list with elements TE, lower, upper, seTE, z, p, level, scale.
• 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).
• 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.

References

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

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="label")