Confidence intervals for Omega Squared

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