domegaSq gives the density, pomegaSq gives the
distribution function, qomegaSq gives the quantile function, and
romegaSq generates random deviates.
Arguments
df1, df2
Degrees of freedom for the numerator and the denominator,
respectively.
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 ufs. If anybody
has the inverse of convert.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.
p
Vector of probabilites (p-values).
n
Desired number of Omega Squared values.
x, q
Vector of quantiles, or, in other words, the value(s) of Omega
Squared.
### Generate 10 random Omega Squared valuesromegaSq(10, 66, 3);
### Probability of findings an Omega Squared### value smaller than .06 if it's 0 in the populationpomegaSq(.06, 66, 3);