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userfriendlyscience (version 0.7.2)

# omegaSqDist: The distribution of Omega Squared

## Description

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

## 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 (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.

## Value

`domegaSq` gives the density, `pomegaSq` gives the distribution function, `qomegaSq` gives the quantile function, and `romegaSq` generates random deviates.

## Details

The functions use `convert.omegasq.to.f` and `convert.f.to.omegasq` to provide the Omega Squared distribution.

`convert.omegasq.to.f`, `convert.f.to.omegasq`, `df`, `pf`, `qf`, `rf`

## Examples

Run this code
``````# NOT RUN {
### 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);

# }
``````

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