These are a number of functions to convert statistics and effect size
measures from/to each other.

## Arguments

chisq, cohensf, cohensfsq, d, etasq, f, logodds, means, omegasq, or, p, r, t, z |
The value of the relevant statistic or effect size. |

ncf |
The value of a noncentrality parameter of the F distribution. |

n, n1, n2, N, ns |
The number of observations that the r or t value is
based on, or the number of observations in each of the two groups for an
anova, or the total number of participants when specifying a noncentrality
parameter. |

df, df1, df2 |
The degrees of freedrom for that statistic (for F, the
first one is the numerator (i.e. the effect), and the second one the
denominator (i.e. the error term). |

proportion |
The proportion of participants in each of the two groups
in a t-test or anova. This is used to compute the sample size in each group
if the group sizes are unknown. Thus, if you only provide df1 and df2 when
converting an F value to a Cohen's d value, equal group sizes are assumed. |

b |
The value of a regression coefficient. |

se, sds |
The standard error of standard errors of the relevant
statistic (e.g. of a regression coefficient) or variables. |

minDim |
The smallest of the number of columns and the number of rows
of the crosstable for which the chisquare is translated to a Cramer's V
value. |

lower.tail |
For the F and chisquare distributions, whether to get the
probability of the lower or upper tail. |

akfEq8 |
When converting Cohen's *d* to *r*, for small sample
sizes, bias is introduced when the commonly suggested formula is used
(Aaron, Kromrey & Ferron, 1998). Therefore, by default, this function uses
different equations depending on the sample size (for n < 50 and for n >
50). When `akfEq8` is set to TRUE or FALSE, the corresponding action is
taken; when `akfEq8` is not logical (i.e. TRUE or FALSE), the function
depends on the sample size. |

var.equal |
Whether to compute the value of *t* or Cohen's
*d* assuming equal variances ('yes'), unequal variances ('no'), or
whether to test for the difference ('test'). |

## Value

The converted value as a numeric value.

## Details

Note that by default, the behavior of `convert.d.to.r`

depends on the
sample size (see Bruce, Kromrey & Ferron, 1998).

## References

Aaron, B. Kromrey J. D. & Ferron, J. (1998) *Equating
"r"-based and "d"-based Effect Size Indices: Problems with a Commonly
Recommended Formula.* Paper presented at the Annual Meeting of the Florida
Educational Research Association (43rd, Orlando, FL, November 2-4, 1998).

## Examples

convert.t.to.r(t=-6.46, n=200);

#> [1] -0.4172246

convert.r.to.t(r=-.41, n=200);

#> [1] -6.325297

### Compute some p-values
convert.t.to.p(4.2, 197);

#> [1] 4.041281e-05

convert.chisq.to.p(5.2, 3);

#> [1] 0.3154489

convert.f.to.p(8.93, 3, 644);

#> [1] 1.6762e-05

### Convert d to r using both equations
convert.d.to.r(d=.2, n1=5, n2=5, akfEq8 = FALSE);

#> [1] 0.09950372

convert.d.to.r(d=.2, n1=5, n2=5, akfEq8 = TRUE);

#> [1] 0.1111111