# omegaSqDist: The distribution of Omega Squared In userfriendlyscience: Quantitative Analysis Made Accessible

## Description

These functions use some conversion to and from the F distribution to provide the Omega Squared distribution.

## Usage

 ```1 2 3 4``` ```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 (p-values). `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 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.

## 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.

## Author(s)

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters <[email protected]>

`convert.omegasq.to.f`, `convert.f.to.omegasq`, `df`, `pf`, `qf`, `rf`
 ```1 2 3 4 5 6``` ```### 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); ```