Skip to contents

Find Statistical Outliers in a Meta-Analysis

find.outliers.Rd

Searches for statistical outliers in meta-analysis results generated by meta functions or the rma.uni in the metafor package.

Usage

find.outliers(x, ...)

Arguments

x

Either (1) an object of class meta, generated by the metabin, metagen, metacont, metamean, metacor, metainc, metarate or metaprop function; or (2) and object of class rma.uni created with the rma.uni function in metafor.

...

Additional parameters for the rma.uni or update.meta function.

Value

Returns the identified outliers and the meta-analysis results when the outliers are removed.

If the provided meta-analysis object is of class meta, the following objects are returned if the results of the function are saved to another object:

  • out.study.fixed: A numeric vector containing the names of the outlying studies when assuming a fixed-effect model.

  • out.study.random: A numeric vector containing the names of the outlying studies when assuming a random-effects model. The \(\tau^{2}\) estimator method.tau is inherited from x.

  • m.fixed: An object of class meta containing the results of the meta-analysis with outliers removed (assuming a fixed-effect model).

  • m.random: An object of class meta containing the results of the meta-analysis with outliers removed (assuming a random-effects model, and using the same method.tau as in the original analysis).

If the provided meta-analysis object is of class rma.uni, the following objects are returned if the results of the function are saved to another object:

  • out.study: A numeric vector containing the names of the outlying studies.

  • m: An object of class rma.uni containing the results of the meta-analysis with outliers removed (using the same settings as in the meta-analysis object provided).

Details

This function searches for outlying studies in a meta-analysis results object. Studies are defined as outliers when their 95% confidence interval lies ouside the 95% confidence interval of the pooled effect.

When outliers are found, the function automatically recalculates the meta-analysis results, using the same settings as in the object provided in x, but excluding the detected outliers.

A forest plot of the meta-analysis with outliers removed can be generated directly by plugging the output of the function into the forest function.

References

Harrer, M., Cuijpers, P., Furukawa, T.A, & Ebert, D. D. (2019). Doing Meta-Analysis in R: A Hands-on Guide. DOI: 10.5281/zenodo.2551803. Chapter 6.2

See also

influence.rma.uni, metainf, baujat

Author

Mathias Harrer & David Daniel Ebert

Examples

if (FALSE) {
library(meta)
library(metafor)
library(dmetar)

# Pool with meta
m1 <- metagen(TE, seTE, data = ThirdWave,
              studlab = ThirdWave$Author, common = FALSE)

# Pool with metafor
m2 <- rma(yi = TE, sei = seTE, data = ThirdWave,
          slab = ThirdWave$Author, method = "PM")

# Find outliers
fo1 <- find.outliers(m1)
fo2 <- find.outliers(m2)

# Show summary
fo1
fo2

# Make forest plot
# Pass additional arguments from meta & metafor's forest function
forest(fo1, prediction = TRUE)
forest(fo2, cex = .8, col = "lightblue")
}