Check model for (non-)normality of residuals.

## Usage

```
check_normality(x, ...)
# S3 method for merMod
check_normality(x, effects = c("fixed", "random"), ...)
```

## Arguments

- x
A model object.

- ...
Currently not used.

- effects
Should normality for residuals (

`"fixed"`

) or random effects (`"random"`

) be tested? Only applies to mixed-effects models. May be abbreviated.

## Value

The p-value of the test statistics. A p-value < 0.05 indicates a significant deviation from normal distribution.

## Details

`check_normality()`

calls `stats::shapiro.test`

and checks the
standardized residuals (or studentized residuals for mixed models) for
normal distribution. Note that this formal test almost always yields
significant results for the distribution of residuals and visual inspection
(e.g. Q-Q plots) are preferable. For generalized linear models, no formal
statistical test is carried out. Rather, there's only a `plot()`

method for
GLMs. This plot shows a half-normal Q-Q plot of the absolute value of the
standardized deviance residuals is shown (being in line with changes in
`plot.lm()`

for R 4.3+).

## Note

For mixed-effects models, studentized residuals, and *not*
standardized residuals, are used for the test. There is also a
`plot()`

-method
implemented in the **see**-package.

## Examples

```
m <<- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
check_normality(m)
#> OK: residuals appear as normally distributed (p = 0.230).
#>
# plot results
if (require("see")) {
x <- check_normality(m)
plot(x)
}
# \dontrun{
# QQ-plot
plot(check_normality(m), type = "qq")
# PP-plot
plot(check_normality(m), type = "pp")
# }
```