This function uses the MBESS functions `conf.limits.ncf()`

(which has been
copied into this package to avoid the dependency on `MBESS`

)
and `convert.ncf.to.omegasq()`

to compute the point estimate and
confidence interval for Omega Squared (which have been lifted out of MBESS to
avoid importing the whole package)

```
confIntOmegaSq(var1, var2, conf.level = 0.95)
# S3 method for confIntOmegaSq
print(x, ..., digits = 2)
```

- var1, var2
The two variables: one should be a factor (or will be made a factor), the other should have at least interval level of measurement. If none of the variables is a factor, the function will look for the variable with the least unique values and change it into a factor.

- conf.level
Level of confidence for the confidence interval.

- x, digits, ...
Respectively the object to print, the number of digits to round to, and any additonal arguments to pass on to the

`print`

function.

A `confIntOmegaSq`

object is returned, with as elements:

- input
The input arguments

- intermediate
Objects generated while computing the output

- output
The output of the function, consisting of:

- output$es
The point estimate

- output$ci
The confidence interval

Formula 16 in Steiger (2004) is used for the conversion in
`convert.ncf.to.omegasq()`

.

Steiger, J. H. (2004). Beyond the F test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast analysis. Psychological Methods, 9(2), 164-82. https://doi.org/10.1037/1082-989X.9.2.164

```
confIntOmegaSq(mtcars$mpg, mtcars$cyl);
#> Omega squared: 95% CI = [.51; .81], point estimate = .71
```