For an effect size analysis, I am noticing that there are differences between Cohen's d, Hedges's g and Hedges' g*.

- Are these three metrics normally very similar?
- What would be a case where they would produce different results?
- Also is it a matter of preference which I use or report with?

## Best Answer

Both Cohen's d and Hedges' g pool variances on the assumption of equal population variances, but g pools using n - 1 for each sample instead of n, which provides a better estimate, especially the smaller the sample sizes. Both d and g are somewhat positively biased, but only negligibly for moderate or larger sample sizes. The bias is reduced using g*. The d by Glass does not assume equal variances, so it uses the sd of a control group or baseline comparison group as the standardizer for the difference between the two means.

These effect sizes and Cliff's and other nonparametric effect sizes are discussed in detail in my book:

Grissom, R. J., & Kim, J, J. (2005). Effect sizes for research: A broad practical approach. Mahwah, NJ: Erlbaum.