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| Cohen's d, which is based on sample averages gives a biased estimate of the population effect size although this is not very great for total sample sizes above 20 (Kline, 2004). When we have small samples (n < 20) Hedge's g is preferred (Hedges and Olkin, 1985). | Cohen's d, which is based on sample averages gives a biased estimate of the population effect size although this is not very great for total sample sizes above 20 (Kline, 2004). When we have small samples (total sample size < 20) Hedge's g is preferred (Hedges and Olkin, 1985). |
How do I compute a Hedge's g from a Cohen's d
The below is taken from here.
An unbiased version of d can be calculated using the following equation adapted from Hedges and Olkin (1985, p.81):
g = approx. d times {1 - ( 3/[4(n1+n2)-9)] ) }
Cohen's d, which is based on sample averages gives a biased estimate of the population effect size although this is not very great for total sample sizes above 20 (Kline, 2004). When we have small samples (total sample size < 20) Hedge's g is preferred (Hedges and Olkin, 1985).
References
Hedges, L.V. and I. Olkin (1985). Statistical Methods for Meta-Analysis. London: Academic Press.
Kline R. B. (2004). Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research. Washington DC: American Psychological Association;