trimfill.meta {meta} | R Documentation |
Trim and fill method for estimating and adjusting for the number and outcomes of missing studies in a meta-analysis.
## Default S3 method: trimfill(x, seTE, left=NULL, ma.fixed=TRUE, type="L", n.iter.max=50, sm=NULL, studlab=NULL, level=0.95, level.comb=0.95, comb.fixed=TRUE, comb.random=TRUE, silent=TRUE, ...) ## S3 method for class 'meta': trimfill(x, seTE, left=NULL, ma.fixed=TRUE, type="L", n.iter.max=50, sm=NULL, studlab=NULL, level=x$level, level.comb=x$level.comb, comb.fixed=x$comb.fixed, comb.random=x$comb.random, silent=TRUE, ...)
x |
An object of class meta , or estimated treatment
effect in individual studies. |
seTE |
Standard error of estimated treatment effect (mandatory if
x not of class meta ). |
left |
A logical indicating whether studies are supposed to be
missing on the left or right side of the funnel plot. If NULL, the
linear regression test for funnel plot symmetry (i.e., function
metabias(..., meth="linreg") ) is used to determine whether
trials are missing on the left or right side. |
ma.fixed |
A logical indicating whether a fixed effect or random effects model is used to estimate the number of missing studies. |
type |
A character indicating which method is used to estimate
the number of missing studies. Either "L" or "R" . |
n.iter.max |
Maximum number of iterations to estimate number of missing studies. |
sm |
An optional character string indicating underlying summary
measure, e.g., "RD" , "RR" , "OR" , "AS" ,
"MD" , "SMD" ; ignored if x is of class
meta . |
studlab |
An optional vector with study labels; ignored if
x is of class meta . |
level |
The level used to calculate confidence intervals for
individual studies. If existing, x$level is used as value for
level ; otherwise 0.95 is used. |
level.comb |
The level used to calculate confidence interval for
the pooled estimate. If existing, x$level.comb is used as
value for level.comb ; otherwise 0.95 is used. |
comb.fixed |
A logical indicating whether a fixed effect meta-analysis should be conducted. |
comb.random |
A logical indicating whether a random effects meta-analysis should be conducted. |
silent |
A logical indicating whether basic information on iterations shown. |
... |
other arguments |
The trim and fill method can be used for estimating and adjusting for the number and outcomes of missing studies in a meta-analysis. The method relies on scrutiny of one side of a funnel plot for asymmetry assumed due to publication bias.
Internally, both fixed effect and random effects models are calculated
regardless of values choosen for arguments comb.fixed
and
comb.random
. Accordingly, the estimate for the random effects
model can be extracted from component TE.random
of an object
of class "meta"
even if comb.random=FALSE
. However, all
functions in R package meta
will adequately consider the values
for comb.fixed
and comb.random
. E.g. function
print.meta
will not print results for the random effects
model if comb.random=FALSE
.
The function metagen
is called internally.
An object of class c("metagen", "meta", "trimfill")
. The object is a
list containing the following components:
studlab, sm, left, ma.fixed, type |
|
n.iter.max, level, level.comb, |
As defined above. |
comb.fixed, comb.random |
|
TE, seTE |
Estimated treatment effect and standard error of individual studies. |
w.fixed, w.random |
Weight of individual studies (in fixed and random effects model). |
TE.fixed, seTE.fixed |
Estimated overall treatment effect and standard error (fixed effect model). |
TE.random, seTE.random |
Estimated overall treatment effect and standard error (random effects model). |
k |
Number of studies combined in meta-analysis. |
Q |
Heterogeneity statistic Q. |
tau |
Square-root of between-study variance (moment estimator of DerSimonian-Laird). |
method |
Pooling method: "Inverse" . |
call |
Function call. |
n.iter |
Actual number of iterations to estimate number of missing studies. |
trimfill |
A logical vector indicating studies that have been added by trim and fill method. |
k0 |
Number of studies added by trim and fill. |
Guido Schwarzer sc@imbi.uni-freiburg.de
Duval S & Tweedie R (2000), A nonparametric "Trim and Fill" method of accounting for publication bias in meta-analysis. Journal of the American Statistical Association, 95, 89–98.
Duval S & Tweedie R (2000), Trim and Fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455–463.
data(Fleiss93) meta1 <- metabin(event.e, n.e, event.c, n.c, data=Fleiss93, sm="OR") tf1 <- trimfill(meta1) summary(tf1) funnel(tf1, pch=ifelse(tf1$trimfill, 1, 16), level=0.95, comb.fixed=TRUE) trimfill(meta1$TE, meta1$seTE, sm=meta1$sm)