trimfill: Generic function for trim-and-fill method

Description

Trim and fill method for estimating and adjusting for the number and outcomes of missing studies in a meta-analysis.

Usage

trimfill(x, ...)

Arguments

An object of class meta, or estimated treatment effect in individual studies.

...

Additional arguments as in par.

Value

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, seTEEstimated treatment effect and standard error of individual studies.
w.fixed, w.randomWeight of individual studies (in fixed and random effects model).
TE.fixed, seTE.fixedEstimated overall treatment effect and standard error (fixed effect model).
TE.random, seTE.randomEstimated overall treatment effect and standard error (random effects model).
kNumber of studies combined in meta-analysis.
QHeterogeneity statistic Q.
tauSquare-root of between-study variance (moment estimator of DerSimonian-Laird).
methodPooling method: "Inverse".
callFunction call.
n.iterActual number of iterations to estimate number of missing studies.
trimfillA logical vector indicating studies that have been added by trim and fill method.
k0Number of studies added by trim and fill.

Details

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.

References

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.

Examples

Run this code

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)

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