metareg.meta {meta} | R Documentation |
Meta-regression
Description
Meta-regression for objects of class meta
. This is a wrapper
function for the R function rma.uni
in the R
package metafor (Viechtbauer 2010).
Usage
## S3 method for class 'meta'
metareg(
x,
formula,
method.tau = x$method.tau,
hakn = x$method.random.ci == "HK",
level.ma = x$level.ma,
intercept = TRUE,
...
)
metareg(x, ...)
## Default S3 method:
metareg(x, ...)
Arguments
x |
An object of class |
formula |
Either a character string or a formula object. |
method.tau |
A character string indicating which method is
used to estimate the between-study variance tau-squared. Either
|
hakn |
A logical indicating whether the method by Hartung and Knapp should be used to adjust test statistics and confidence intervals. |
level.ma |
The level used to calculate confidence intervals for parameter estimates in the meta-regression model. |
intercept |
A logical indicating whether an intercept should be included in the meta-regression model. |
... |
Additional arguments passed to R function
|
Details
This R function is a wrapper function for R function
rma.uni
in the R package metafor
(Viechtbauer 2010).
Note, results are not back-transformed in printouts of
meta-analyses using summary measures with transformations, e.g.,
log risk ratios are printed instead of the risk ratio if argument
sm = "RR"
and logit transformed proportions are printed if
argument sm = "PLOGIT"
.
Argument '...' can be used to pass additional arguments to R
function rma.uni
. For example, argument
control
to provide a list of control values for the
iterative estimation algorithm. See help page of R function
rma.uni
for more details.
Value
An object of class c("metareg", "rma.uni", "rma")
. Please
look at the help page of R function rma.uni
for more details on the output from this function.
In addition, a list .meta
is added to the output containing
the following components:
x , formula , method.tau , hakn , level.ma , intercept |
As defined above. |
dots |
Information provided in argument '...'. |
call |
Function call. |
version |
Version of R package meta used to create object. |
version.metafor |
Version of R package metafor used to create object. |
Author(s)
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
References
Viechtbauer W (2010): Conducting Meta-Analyses in R with the Metafor Package. Journal of Statistical Software, 36, 1–48
See Also
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")
## Not run:
# Error due to wrong ordering of arguments (order has changed in
# R package meta, version 3.0-0)
#
try(metareg(~ region, m1))
try(metareg(~ region, data = m1))
# Warning as no information on covariate is available
#
metareg(m1)
## End(Not run)
# Do meta-regression for covariate region
#
mu2 <- update(m1, subgroup = region, tau.common = TRUE, common = FALSE)
metareg(mu2)
# Same result for
# - tau-squared
# - test of heterogeneity
# - test for subgroup differences
# (as argument 'tau.common' was used to create mu2)
#
mu2
metareg(mu2, intercept = FALSE)
metareg(m1, region)
# Different result for
# - tau-squared
# - test of heterogeneity
# - test for subgroup differences
# (as argument 'tau.common' is - by default - FALSE)
#
mu1 <- update(m1, subgroup = region)
mu1
# Generate bubble plot
#
bubble(metareg(mu2))
# Do meta-regression with two covariates
#
metareg(mu1, region + age)
# Do same meta-regressions using formula notation
#
metareg(m1, ~ region)
metareg(mu1, ~ region + age)
# Do meta-regression using REML method and print intermediate
# results for iterative estimation algorithm; furthermore print
# results with three digits.
#
metareg(mu1, region, method.tau = "REML",
control = list(verbose = TRUE), digits = 3)
# Use Hartung-Knapp method
#
mu3 <- update(mu2, method.random.ci = "HK")
mu3
metareg(mu3, intercept = FALSE)