Searches for statistical outliers in meta-analysis results generated by `meta`

functions or the
`rma.uni`

in the `metafor`

package.

## Arguments

- x
Either (1) an object of class

`meta`

, generated by the`metabin`

,`metagen`

,`metacont`

,`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\

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

## Examples

```
if (FALSE) {
suppressPackageStartupMessages(library(meta))
suppressPackageStartupMessages(library(metafor))
suppressPackageStartupMessages(library(dmetar))
# Pool with meta
m1 <- metagen(TE, seTE, data = ThirdWave,
studlab = ThirdWave$Author, comb.fixed = FALSE)
# Pool with metafor
m2 <- rma(yi = TE, sei = seTE, data = ThirdWave,
slab = ThirdWave$Author, method = "PM")
# Find outliers
fo1 <- find.outliers(m1)
fo2 <- find.outliers(m2)
# Show summary
summary(fo1)
summary(fo2)
# Make forest plot
# Pass additional arguments from meta & metafor's forest function
forest(fo1, prediction = TRUE)
forest(fo2, cex = .8, col = "lightblue")
}
```