omegaSqDist
These functions use some conversion to and from the F distribution to provide the Omega Squared distribution.
 Keywords
 univar
Usage
domegaSq(x, df1, df2, populationOmegaSq = 0)
pomegaSq(q, df1, df2, populationOmegaSq = 0, lower.tail = TRUE)
qomegaSq(p, df1, df2, populationOmegaSq = 0, lower.tail = TRUE)
romegaSq(n, df1, df2, populationOmegaSq = 0)
Arguments
 x, q
 Vector of quantiles, or, in other words, the value(s) of Omega Squared.
 p
 Vector of probabilites (pvalues).
 df1, df2
 Degrees of freedom for the numerator and the denominator, respectively.
 n
 Desired number of Omega Squared values.
 populationOmegaSq

The value of Omega Squared in the population; this determines the center of the Omega Squared distribution. This has not been implemented yet in this version of
userfriendlyscience
. If anybody has the inverse ofconvert.ncf.to.omegasq
for me, I'll happily integrate this.  lower.tail
 logical; if TRUE (default), probabilities are the likelihood of finding an Omega Squared smaller than the specified value; otherwise, the likelihood of finding an Omega Squared larger than the specified value.
Details
The functions use convert.omegasq.to.f
and convert.f.to.omegasq
to provide the Omega Squared distribution.
Value
domegaSq
gives the density, pomegaSq
gives the distribution function, qomegaSq
gives the quantile function, and romegaSq
generates random deviates.
See Also
Examples
### Generate 10 random Omega Squared values
romegaSq(10, 66, 3);
### Probability of findings an Omega Squared
### value smaller than .06 if it's 0 in the population
pomegaSq(.06, 66, 3);
Community examples
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