metabind: Combine and summarize meta-analysis objects

In meta: General Package for Meta-Analysis

Combine and summarize meta-analysis objects

Description

This function can be used to combine meta-analysis objects and is, for example, useful to summarize results of various meta-analysis methods or to generate a forest plot with results of several subgroup analyses.

Usage

metabind(
  ...,
  subgroup = NULL,
  name = NULL,
  common = NULL,
  random = NULL,
  prediction = NULL,
  backtransf = NULL,
  outclab = NULL,
  pooled = NULL,
  warn.deprecated = gs("warn.deprecated")
)

Arguments

...	Any number of meta-analysis objects or a single list with meta-analyses.
subgroup	An optional variable to generate a forest plot with subgroups.
name	An optional character vector providing descriptive names for the meta-analysis objects.
common	A logical vector indicating whether results of common effect model should be considered.
random	A logical vector indicating whether results of random effects model should be considered.
prediction	A logical vector indicating whether results of prediction intervals should be considered.
backtransf	A logical indicating whether results should be back transformed in printouts and plots. If backtransf=TRUE (default), results for sm="OR" are printed as odds ratios rather than log odds ratios, for example.
outclab	Outcome label for all meta-analyis objects.
pooled	Deprecated argument (replaced by common and random.
warn.deprecated	A logical indicating whether warnings should be printed if deprecated arguments are used.

Details

This function can be used to combine any number of meta-analysis objects which is useful, for example, to summarize results of various meta-analysis methods or to generate a forest plot with results of several subgroup analyses (see Examples).

Individual study results are not retained with metabind as the function allows to combine meta-analyses from different data sets (e.g., with randomised or observational studies). Individual study results are retained with R function metamerge which can be used to combine results of meta-analyses of the same dataset.

Value

An object of class c("metabind", "meta") with corresponding generic functions (see meta-object).

Author(s)

Guido Schwarzer [e-mail]

See Also

metagen, forest.metabind, metamerge

Examples

data(Fleiss1993cont)

# Add some (fictitious) grouping variables:
#
Fleiss1993cont$age <- c(55, 65, 55, 65, 55)
Fleiss1993cont$region <- c("Europe", "Europe", "Asia", "Asia", "Europe")

m1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
  data = Fleiss1993cont, sm = "SMD")

# Conduct two subgroup analyses
#
mu1 <- update(m1, subgroup = age, subgroup.name = "Age group")
mu2 <- update(m1, subgroup = region, subgroup.name = "Region")

# Combine random effects subgroup meta-analyses and show forest
# plot with subgroup results
#
mb1 <- metabind(mu1, mu2, common = FALSE)
mb1
forest(mb1)

# Use various estimation methods for between-study heterogeneity
# variance
#
m1.pm <- update(m1, method.tau = "PM")
m1.dl <- update(m1, method.tau = "DL")
m1.ml <- update(m1, method.tau = "ML")
m1.hs <- update(m1, method.tau = "HS")
m1.sj <- update(m1, method.tau = "SJ")
m1.he <- update(m1, method.tau = "HE")
m1.eb <- update(m1, method.tau = "EB")

# Combine meta-analyses and show results
#
taus <- c("Restricted maximum-likelihood estimator",
  "Paule-Mandel estimator",
  "DerSimonian-Laird estimator",
  "Maximum-likelihood estimator",
  "Hunter-Schmidt estimator",
  "Sidik-Jonkman estimator",
  "Hedges estimator",
  "Empirical Bayes estimator")
#
m1.taus <- metabind(m1, m1.pm, m1.dl, m1.ml, m1.hs, m1.sj, m1.he, m1.eb,
  name = taus, common = FALSE)
m1.taus
forest(m1.taus)

meta documentation built on Oct. 31, 2024, 5:07 p.m.