Performs an influence analysis. Pooled estimates are calculated omitting one study at a time.
metainf(x, pooled, sortvar)
An object of class meta
.
A character string indicating whether a fixed effect
or random effects model is used for pooling. Either missing (see
Details), "fixed"
or "random"
, can be abbreviated.
An optional vector used to sort the individual
studies (must be of same length as x$TE
).
An object of class c("metainf", "meta")
with corresponding
print
, and forest
functions. The object is a list
containing the following components:
Estimated treatment effect and standard error of pooled estimate in influence analysis.
Lower and upper confidence interval limits.
Study label describing omission of studies.
P-value for test of overall effect.
Sum of weights from fixed effect or random effects model.
Heterogeneity statistic I2.
Heterogeneity statistic Rb.
Square-root of between-study variance.
Degrees of freedom for test of treatment effect for
Hartung-Knapp method (only if hakn = TRUE
).
Summary measure.
Method used for pooling.
Number of studies combined in meta-analysis.
As defined above.
A logical indicating whether analysis is based on fixed effect model.
A logical indicating whether analysis is based on random effects model.
Value is NA
.
Value is NA
.
Value is NA
.
The level used to calculate confidence intervals for pooled estimates.
A logical indicating whether the method by Hartung and Knapp is used to adjust test statistics and confidence intervals.
A character string indicating which method is
used to estimate the between-study variance
Prespecified value for the square-root of the
between-study variance
Overall treatment effect used to estimate the
between-study variance
Harmonic mean of number of observations (for back transformation of Freeman-Tukey Double arcsine transformation).
Version of R package meta used to create object.
Performs a influence analysis; pooled estimates are calculated
omitting one study at a time. Studies are sorted according to
sortvar
.
Information from object x
is utilised if argument
pooled
is missing. A fixed effect model is assumed
(pooled="fixed"
) if argument x$comb.fixed
is
TRUE
; a random effects model is assumed
(pooled="random"
) if argument x$comb.random
is
TRUE
and x$comb.fixed
is FALSE
.
Cooper H & Hedges LV (1994): The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation
# NOT RUN {
data(Fleiss93)
m1 <- metabin(event.e, n.e, event.c, n.c,
data = Fleiss93, 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 = "Fleiss93 meta-analysis",
backtransf = FALSE)
metainf(m2)
data(Fleiss93cont)
m3 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c,
data = Fleiss93cont, sm = "SMD")
metainf(m3)
# }
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