meta (version 3.0-1)

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

x

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, 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.
• 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.

Details

The trim and fill method (Duval, Tweedie 2000a, 2000b) 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. For more details, see help page of R function trimfill.meta.

References

Duval S & Tweedie R (2000a), 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 (2000b), Trim and Fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455--463.

See Also

metagen, metabias, trimfill.meta, funnel

Examples

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)