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meta (version 0.5)

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

Description

Print and summary method for objects of class meta.

Usage

print.meta(x, sortvar, level=0.95, level.comb=level,
           details=FALSE, ma=TRUE, digits=max(4, .Options$digits - 3), ...)

summary.meta(object, byvar, bylab, bystud=FALSE, level.comb=0.95, ...)

print.summary.meta(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.
...
other arguments

Value

  • A list is returned by the function summary.meta with the following elements:
  • fixedResults for fixed effect model (a list with elements TE, seTE, lower, upper, z, p, level).
  • randomResults for random effects model (a list with elements TE, seTE, lower, upper, z, p, level).
  • randomA list with elements TE, lower, upper, seTE, z, p, level, scale.
  • kNumber of studies combined in meta-analysis.
  • QHeterogeneity statistic Q.
  • tauSquare-root of between-study variance (moment estimator of DerSimonian-Laird).
  • HHeterogeneity statistic H (a list with elements TE, lower, upper).
  • I2Heterogeneity statistic I2 (a list with elements TE, lower, upper).
  • k.allTotal number of trials.
  • Q.CMHCochrane-Mantel-Haenszel heterogeneity statistic.
  • smA character string indicating underlying summary measure.
  • methodA character string with the pooling method.
  • callFunction call.
  • ci.labLabel for confidence interval.
  • withinResults within groups (a list with elements TE, seTE, lower, upper, z, p, level) - 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.
  • bylabLabel for grouping variable - if byvar is not missing.
  • by.levsLevels 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

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(meta1, byvar=c(1,2,1,1,2), bylab="label")

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