Description Usage Arguments Details Value References Examples

Corrects a vector of Cohen's *d* values for small-sample bias, as Cohen's *d*
has a slight positive bias. The bias-corrected *d* value is often called
Hedges's *g*.

1 | ```
correct_d_bias(d, n)
``` |

`d` |
Vector of Cohen's d values. |

`n` |
Vector of sample sizes. |

The bias correction is: \mjdeqng = d_c = d_obs \times Jg = d_c = d * J

where \mjdeqnJ = \frac\Gamma(\fracn - 22)\sqrt\fracn - 22 \times \Gamma(\fracn - 32)J = \Gamma((n - 2) / 2) / (sqrt(n - 2) * \Gamma((n - 2) / 2))

and \mjeqnd_obsd is the observed effect size, \mjeqng = d_cg = d_c is the corrected (unbiased) estimate, \mjseqnn is the total sample size, and \mjeqn\Gamma()\Gamma() is the gamma function.

Historically, using the gamma function was computationally intensive, so an approximation for \mjseqnJ was used (Borenstein et al., 2009): \mjdeqnJ = 1 - 3 / (4 * (n - 2) - 1)J = 1 - 3 / (4 * (n - 2) - 1

This approximation is no longer necessary with modern computers.

Vector of g values (d values corrected for small-sample bias).

Hedges, L. V., & Olkin, I. (1985).
*Statistical methods for meta-analysis*.
Academic Press. p. 104

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009).
*Introduction to meta-analysis*.
Wiley. p. 27.

1 2 3 | ```
correct_d_bias(d = .3, n = 30)
correct_d_bias(d = .3, n = 300)
correct_d_bias(d = .3, n = 3000)
``` |

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