Hedges’ g Effect Size Calculator
Enter summary statistics for two independent groups. This tool computes pooled SD, Cohen’s d, Hedges’ g, and a 95% confidence interval.
What Is Hedges’ g?
Hedges’ g is a standardized mean difference used to estimate effect size between two groups. It is very similar to Cohen’s d, but includes a small-sample correction so the estimate is less biased when total sample size is modest.
If you compare an intervention group to a control group, Hedges’ g tells you how many pooled standard deviations apart the two means are.
Why Use Hedges’ g Instead of Cohen’s d?
- Less bias in smaller samples: Cohen’s d tends to overestimate the true population effect when samples are small.
- Common in meta-analysis: Many systematic reviews and meta-analyses report Hedges’ g as the default effect size metric.
- Comparable interpretation: You can still interpret magnitudes similarly (small, medium, large), while getting a corrected estimate.
Formula Used in This Calculator
1) Pooled Standard Deviation
2) Cohen’s d
3) Small-Sample Correction Factor
4) Hedges’ g
How to Interpret Hedges’ g
A common rule of thumb for the absolute value of Hedges’ g:
- ~0.20 = small effect
- ~0.50 = medium effect
- ~0.80 = large effect
Direction also matters: a positive value means Group 1 is higher than Group 2, while a negative value means Group 1 is lower.
When This Calculator Is Appropriate
- Two independent groups (not paired/repeated measures).
- You have summary stats: mean, standard deviation, and sample size for each group.
- You want a standardized effect size for research reports or meta-analytic work.
Reporting Example
You can report your result like this:
“The treatment group scored higher than the control group, with a Hedges’ g of 0.47 (95% CI [0.10, 0.84]), indicating a small-to-moderate effect.”
Practical Notes
Confidence Interval
The calculator provides an approximate 95% confidence interval. Wider intervals indicate more uncertainty, usually because of smaller samples or high variability.
Assumptions
- Groups are independent.
- Data are measured on roughly continuous scales.
- Standard deviations are meaningful for each group.
Bottom Line
Hedges’ g gives a corrected, easy-to-compare estimate of group differences. If you are working with smaller samples or preparing evidence for publication, it is usually a better default than Cohen’s d.