metamerge: Merge pooled results of two meta-analyses

View source: R/metamerge.R

metamergeR Documentation

Merge pooled results of two meta-analyses

Description

This function can be used to merge pooled results of two meta-analyses into a single meta-analysis object. This is, for example, useful to produce a forest plot of a random-effects meta-analysis with different estimates of the between-study variance τ^2.

Usage

metamerge(
  meta1,
  meta2,
  pooled1,
  pooled2,
  text.pooled1,
  text.pooled2,
  text.w.pooled1,
  text.w.pooled2,
  label1,
  label2,
  backtransf
)

Arguments

meta1

First meta-analysis object (see Details).

meta2

Second meta-analysis object (see Details).

pooled1

A character string indicating whether results of common effect or random effects model should be considered for first meta-analysis. Either "both", "common" or "random", can be abbreviated.

pooled2

A character string indicating whether results of common effect or random effects model should be considered for second meta-analysis. Either "both", "common" or "random", can be abbreviated.

text.pooled1

A character string used in printouts and forest plot to label the results from the first meta-analysis.

text.pooled2

A character string used in printouts and forest plot to label the results from the second meta-analysis.

text.w.pooled1

A character string used to label weights of the first meta-analysis.

text.w.pooled2

A character string used to label weights of the second meta-analysis.

label1

A character string used to label estimate of between-study variance and heterogeneity statistics of the first meta-analysis.

label2

A character string used to label estimate of between-study variance and heterogeneity statistics of the second meta-analysis.

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.

Details

In R package meta, objects of class "meta" contain results of both a common effect and random effects meta-analysis. This function enables the user to keep the results of one of these models and to add results from a second meta-analysis or a sensitivity analysis.

Applications of this function include printing and plotting results of the common effect or random effects meta-analysis and the

  • trim-and-fill method (trimfill),

  • limit meta-analyis (limitmeta from R package metasens),

  • Copas selection model (copas from R package metasens),

  • robust variance meta-analysis model (robu from R package robumeta).

The first argument must be an object created by a meta-analysis function, e.g., metagen or metabin. It is also possible to provide an object created with limitmeta or copas. In this case, arguments meta2 and pooled2 will be ignored.

The second meta-analysis could be an object created by a meta-analysis function or with trimfill, limitmeta, copas, or robu.

The created meta-analysis object only contains the study results from the first meta-analysis which are shown in printouts and forest plots. This only makes a difference for meta-analysis methods where individual study results differ, e.g., Mantel-Haenszel and Peto method for binary outcomes (see metabin).

R function metabind can be used to print and plot the results of more than two meta-analyses, however, without showing individual study results.

Value

An object of class "meta" and "metamerge" with corresponding generic functions (see meta-object).

The following list elements have a different meaning:

TE, seTE, studlab

Treatment estimate, standard error, and study labels (first meta-analyis).

lower, upper

Lower and upper confidence interval limits for individual studies (first meta-analysis).

statistic, pval

Statistic and p-value for test of treatment effect for individual studies (first meta-analysis.

w.common

Weights of first common effect meta-analysis.

w.random

Weights of first random effects meta-analysis.

k

Number of studies combined in first meta-analysis.

Furthermore, meta-analysis results of common effect or random effects model are taken from first meta-analysis if only random effects or common effects models are selected from both meta-analyses (arguments pooled1 and pooled2).

Author(s)

Guido Schwarzer sc@imbi.uni-freiburg.de

See Also

metagen, metabind

Examples

data(Fleiss1993cont)
#
m1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
  data = Fleiss1993cont, sm = "MD",
  text.random = "Random effects model (REML)", text.w.random = "DL")
#
# Use DerSimonian-Laird estimator of tau2
#
m2 <- update(m1, method.tau = "DL", common = FALSE,
  text.random = "Random effects model (DL)", text.w.random = "DL")
#
# Merge results of the two meta-analyses
#
m12 <- metamerge(m1, m2)
m12
forest(m12, rightcols = c("effect", "ci", "w.common"))

# Show in addition the results for the Paule-Mandel estimate of
# between-study variance
#
m3 <- update(m1, method.tau = "PM",
  text.random = "Random effects moded (PM)", text.w.random = "PM")
#
m123 <- metamerge(m12, m3, pooled2 = "random")
m123

data(Fleiss1993bin)
#
# Mantel-Haenszel method
#
m4 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin,
  studlab = paste(study, year), sm = "OR", random = FALSE,
  text.common = "MH method", text.w.common = "MH")
#
# Peto method
#
m5 <- update(m4, method = "Peto", text.common = "Peto method",
  text.w.common = "Peto")
#
# Merge results (show individual results for MH method)
#
m45 <- metamerge(m4, m5)
summary(m45)
forest(m45, digits = 4)
#
# Merge results (show individual results for Peto method)
#
m54 <- metamerge(m5, m4)
summary(m54)
forest(m54)


meta documentation built on Sept. 18, 2022, 1:06 a.m.