metaadd | R Documentation |
Add pooled results from external analysis to an existing meta-analysis object. This is useful, for example, to add results from a Bayesian meta-analysis which is not implemented in R package meta.
metaadd(
x,
type,
TE,
lower,
upper,
statistic = NA,
pval = NA,
text,
data = NULL,
method.common = "",
method.random = "",
method.tau = "",
method.random.ci = "",
method.predict = "",
transf = gs("transf")
)
x |
Meta-analysis object. |
type |
A character string or vector indicating whether added
results are from common effect, random effects model or
prediction interval. Either |
TE |
Pooled estimate(s). |
lower |
Lower limit(s) of confidence or prediction interval. |
upper |
Upper limit(s) of confidence or prediction interval. |
statistic |
Test statistic(s). |
pval |
P-value(s). |
text |
A character string or vector used in printouts and forest plot to label the added results. |
data |
An optional data frame containing the new results or an
object of class |
method.common |
A character string or vector to describe the common effect method(s). |
method.random |
A character string or vector to describe the random effects method(s). |
method.tau |
A character string or vector to describe the estimator(s) of the between-study variance. |
method.random.ci |
A character string or vector to describe the method(s) to calculate confidence intervals under the random effects model. |
method.predict |
A character string or vector to describe the method(s) used for prediction intervals. |
transf |
A logical indicating whether inputs for arguments
|
In R package meta, objects of class "meta"
contain
results of both common effect and random effects
meta-analyses. This function enables the user to add the pooled
results of an additional analysis to an existing meta-analysis
object. This is useful, for example, to add the result of a
Bayesian meta-analysis.
If argument data
is a meta-analysis object created with R
package meta, arguments TE
, lower
,
upper
, statistic
and pval
are ignored as this
information is extracted from the meta-analysis.
Otherwise, arguments TE
, lower
and upper
have
to be provided if type = "common"
or type =
"random"
. For type = "prediction"
, only arguments
lower
and upper
are mandatory.
Note, R function metamerge
can be used to add
meta-analysis results of another meta-analysis object (see
meta-object
).
An object of class "meta"
with corresponding generic
functions (see meta-object
).
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
metagen
, metamerge
data(Fleiss1993bin)
# Common effect and random effects meta-analysis
m1 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin,
studlab = paste(study, year), sm = "OR")
# Naive pooling
m2 <- metabin(sum(d.asp), sum(n.asp), sum(d.plac), sum(n.plac),
data = Fleiss1993bin, sm = "OR", text.common = "Naive pooling")
# Add results of second meta-analysis from common effect model
m12 <- metaadd(m1, data = m2, method.common = "Naive pooling")
m12
forest(m12)
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