metainf.meta | R Documentation |
Performs an influence analysis. Pooled estimates are calculated omitting one study at a time.
## S3 method for class 'meta'
metainf(x, pooled, sortvar, no = 1, ...)
metainf(x, ...)
## Default S3 method:
metainf(x, ...)
x |
An object of class |
pooled |
A character string indicating whether a common effect
or random effects model is used for pooling. Either missing (see
Details), |
sortvar |
An optional vector used to sort the individual
studies (must be of same length as |
no |
A numeric specifying which meta-analysis results to consider. |
... |
Additional arguments (ignored). |
Performs a influence analysis; pooled estimates are calculated
omitting one study at a time. Studies are sorted according to
sortvar
.
Information from object x
is utilised if argument
pooled
is missing. A common effect model is assumed
(pooled="common"
) if argument x$common
is
TRUE
; a random effects model is assumed
(pooled="random"
) if argument x$random
is
TRUE
and x$common
is FALSE
.
An object of class "meta"
and "metainf"
with
corresponding generic functions (see meta-object
).
The following list elements have a different meaning:
TE , seTE |
Estimated treatment effect and standard error of pooled estimate in influence analysis. |
lower , upper |
Lower and upper confidence interval limits. |
statistic |
Statistic for test of overall effect. |
pval |
P-value for test of overall effect. |
studlab |
Study label describing omission of studies. |
w |
Sum of weights from common effect or random effects model. |
TE.common , seTE.common |
Value is |
TE.random , seTE.random |
Value is |
Q |
Value is |
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
Cooper H & Hedges LV (1994): The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation
metabin
, metacont
,
print.meta
data(Fleiss1993bin)
m1 <- metabin(d.asp, n.asp, d.plac, n.plac,
data = Fleiss1993bin, studlab = study, sm = "RR", method = "I")
m1
metainf(m1)
metainf(m1, pooled = "random")
forest(metainf(m1))
forest(metainf(m1), layout = "revman5")
forest(metainf(m1, pooled = "random"))
metainf(m1, sortvar = study)
metainf(m1, sortvar = 7:1)
m2 <- update(m1, title = "Fleiss1993bin meta-analysis", backtransf = FALSE)
metainf(m2)
data(Fleiss1993cont)
m3 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
data = Fleiss1993cont, sm = "SMD")
metainf(m3)
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