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)

## Arguments

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.

## Value

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

## Note

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

## References

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

## Author

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

## Examples


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