metafor (version 1.4-0)

trimfill.rma.uni: Trim and Fill Method for rma.uni Objects

Description

Apply the trim and fill method to objects of class "rma.uni".

Usage

## S3 method for class 'rma.uni':
trimfill(x, estimator="L0", side=NULL, maxit=50, verbose=FALSE, \dots)

Arguments

x

an object of class "rma.uni".

estimator

either "L0" or "R0" indicating the estimator to use for estimating the number of missing studies.

side

either "left", "right", or NULL indicating on which side of the funnel plot the missing studies should be imputed. If NULL, the side is chosen within the function depending on the results of Egger's regr

maxit

an integer value indicating the maximum number of iterations to use for the trim and fill method.

verbose

logical indicating whether information about the evolution of the algorithm should be printed.

...

other arguments.

Value

• An object of class c("rma.uni.trimfill","rma.uni","rma"). The object is a list containing the same components as objects created by rma.uni, except that the data are augmented by the trim and fill method. The object also contains a vector of dummy codes (called fill), indicating which of the data are the observed (0) and the augmented (1) data. Calling funnel.rma on the object provides a funnel plot of the observed and augmented data.

Details

The trim and fill method is a nonparametric (rank-based) data augmentation technique proposed by Duval and Tweedie (2000a, 2000b; see also Duval, 2005). The method can be used to estimate the number of studies missing from a meta-analysis due to the suppression of the most extreme results on one side of the funnel plot. The method then augments the observed data so that the funnel plot is more symmetric. The trim and fill method can only be used in the context of the fixed- or random-effects model (i.e., in models without moderators). The method should not be regarded as a way of yielding a more "valid" estimate of the overall effect or outcome, but as a way of examining the sensitivity of the results to one particular selection mechanism (i.e., one particular form of publication bias).

References

Duval, S. J. & Tweedie, R. L. (2000a). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455--463. Duval, S. J. & Tweedie, R. L. (2000b). 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. J. (2005). The trim and fill method. In H. R. Rothstein, A. J. Sutton & M. Borenstein (Eds.) (2005) Publication bias in meta-analysis: Prevention, assessment, and adjustments (pp. 127--144). Chichester, England: Wiley. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1--48. http://www.jstatsoft.org/v36/i03/.

See Also

funnel.rma

Examples

### load BCG vaccine data
data(dat.bcg)

### meta-analysis of the log relative risks using a fixed-effects model
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, 
           data=dat.bcg, measure="RR", method="FE")
trimfill(res)
funnel(trimfill(res))

### meta-analysis of the log relative risks using a random-effects model
res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg, 
           data=dat.bcg, measure="RR", method="REML")
trimfill(res)
funnel(trimfill(res))