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metafor (version 1.9-4)

leave1out: Leave-One-Out Diagnostics for 'rma' Objects

Description

The functions repeatedly fit the specified model, leaving out one observation/study at a time.

Usage

leave1out(x, ...)

## S3 method for class 'rma.uni':
leave1out(x, digits, transf, targs, \dots)
## S3 method for class 'rma.mh':
leave1out(x, digits, transf, targs, \dots)
## S3 method for class 'rma.peto':
leave1out(x, digits, transf, targs, \dots)

Arguments

x
an object of class "rma.mh", "rma.peto", or "rma.uni".
digits
integer specifying the number of decimal places to which the printed results should be rounded (if unspecified, the default is to take the value from the object).
transf
an optional argument specifying the name of a function that should be used to transform the model coefficients and interval bounds (e.g., transf=exp). If unspecified, no transformation is used.
targs
optional arguments needed by the function specified under transf.
...
other arguments.

Value

  • An object of class "list.rma". The object is a list containing the following components:
  • estimateestimated coefficients of the model.
  • sestandard errors of the coefficients.
  • zvaltest statistics of the coefficients.
  • pvalp-values for the test statistics.
  • ci.lblower bounds of the confidence intervals for the coefficients.
  • ci.ubupper bounds of the confidence intervals for the coefficients.
  • Qtest statistics for the tests of heterogeneity.
  • Qpp-values for the tests of heterogeneity.
  • tau2estimated amounts of (residual) heterogeneity (only for random-effects models).
  • I2values of latex{$I^2$}html{$I²$}text{$I^2$} (only for random-effects models).
  • H2values of latex{$H^2$}html{$H²$}text{$H^2$} (only for random-effects models).
  • The "list.rma" object is formated and printed with print.list.rma.

Details

The model specified by x must be a model without moderators (i.e., either a fixed- or a random-effects model).

References

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/. Viechtbauer, W., & Cheung, M. W.-L. (2010). Outlier and influence diagnostics for meta-analysis. Research Synthesis Methods, 1, 112--125.

See Also

rma.uni, rma.mh, rma.peto

Examples

Run this code
### load BCG vaccine data
data(dat.bcg)

### calculate log relative risks and corresponding sampling variances
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### random-effects model
res <- rma(yi, vi, data=dat)

### cumulative meta-analysis
leave1out(res)
leave1out(res, transf=exp)

### meta-analysis of the (log) relative risks using the Mantel-Haenszel method
res <- rma.mh(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### cumulative meta-analysis
leave1out(res)
leave1out(res, transf=exp)

### meta-analysis of the (log) odds ratios using Peto's method
res <- rma.peto(ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)

### cumulative meta-analysis
leave1out(res)
leave1out(res, transf=exp)

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