`plot.vif.rma.Rd`

Plot method for objects of class `"vif.rma"`

.

- x
an object of class

`"vif.rma"`

obtained with`vif`

.- breaks
argument to be passed on to the corresponding argument of

`hist`

to set (the method for determining) the (number of) breakpoints.- freq
logical to indicate whether frequencies or probability densities should be plotted (the default is

`FALSE`

to plot densities).- col
character string to specify the color for the bars (the default is gray).

- border
character string to specify the color for the border around the bars (the default is white).

- trim
the fraction (up to 0.5) of observations to be trimmed from the upper tail of each distribution before its histogram is plotted.

- col.out
character string to specify the color for the bars that are more extreme than the observed (G)VIF value (the default is a semi-transparent shade of red).

- col.density
character string to specify the color of the kernel density estimate of the distribution that is superimposed on top of the histogram (the default is blue).

- adjust
numeric value to be passed on to the corresponding argument of

`density`

(for adjusting the bandwidth of the kernel density estimate).- lwd
numeric vector to specify the width of the vertical lines corresponding to the value of the observed (G)VIFs and of the density estimate (note: by default, the density estimate has a line width of 0 and is therefore not plotted).

- layout
optional vector of two numbers to specify the number of rows and columns for the layout of the figure.

- ...
other arguments.

The function plots the distribution of each (G)VIF as simulated under independence as a histogram.

Arguments `breaks`

, `freq`

, `col`

, and `border`

are passed on to the `hist`

function for the plotting.

Argument `trim`

can be used to trim away a certain fraction of observations from the upper tail of each distribution before its histogram is plotted. By setting this to a value above 0, one can quickly remove some of the extreme values that might lead to the bulk of the distribution getting squished together at the left (typically, a small value such as `trim=.01`

is sufficient for this purpose).

The observed (G)VIF value is indicated as a vertical dashed line. If the observed exceeds the upper plot limit, then this is indicated by an arrow pointing to the line.

Argument `col.out`

is used to specify the color for the bars in the histogram that are more extreme than the observed (G)VIF value.

A kernel density estimate of the distribution can be superimposed on top of the histogram (as a smoothed representation of the distribution). Note that the kernel density estimate of the distribution is only shown when setting the line width for this element greater than 0 via the `lwd`

argument (e.g., `lwd=c(2,2)`

).

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. *Journal of Statistical Software*, **36**(3), 1–48. https://doi.org/10.18637/jss.v036.i03

`vif.rma`

for the function to create `vif.rma`

objects.

```
### copy data from Bangert-Drowns et al. (2004) into 'dat'
dat <- dat.bangertdrowns2004
### fit mixed-effects meta-regression model
res <- rma(yi, vi, mods = ~ length + wic + feedback + info + pers + imag + meta, data=dat)
#> Warning: Studies with NAs omitted from model fitting.
### use the simulation approach to analyze the size of the VIFs
# \dontrun{
vifs <- vif(res, sim=TRUE)
vifs
#>
#> vif prop
#> length 1.5371 0.96
#> wic 1.3860 0.87
#> feedback 1.6490 0.99
#> info 1.8340 0.98
#> pers 5.6780 1.00
#> imag 1.1554 0.48
#> meta 4.5333 1.00
#>
### plot the simulated distributions of the VIFs
plot(vifs)
### add densities, trim away some extremes, and set break points
plot(vifs, lwd=c(2,2), trim=.01, breaks=seq(1,2.2,by=.05), adjust=1.5)
# }
```