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Hedges' g Effect Size Calculator

Bias-corrected standardised mean difference from two groups’ means, SDs and sizes — Hedges’ g, Cohen’s d, the correction factor and a 95% confidence interval.

Group 1 mean

Group 1 SD

Group 1 n

Group 2 mean

Group 2 SD

Group 2 n

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How it works

d = (M₁ − M₂) ÷ s_pooled; J = 1 − 3 ÷ (4(n₁+n₂) − 9); g = J·d; SE(g) ≈ √[(n₁+n₂)/(n₁n₂) + g²/2(n₁+n₂)]

Cohen's d overestimates the population effect in small samples because the pooled SD is a biased estimator. Hedges' g multiplies d by a correction factor J that depends only on the degrees of freedom — about 0.97 at 25 subjects total and essentially 1 beyond 50. Meta-analyses report g for this reason. The same small/medium/large benchmarks (0.2/0.5/0.8) apply.

Worked example

Means 52.3 vs 45.1, SDs 9.8 and 10.4, n = 12 and 11: pooled SD 10.1, d = 0.71, J = 0.964, g = 0.69 (medium), 95% CI −0.16 to 1.53.

Frequently asked questions

When does the correction matter?

Below about 20 per group. At 50 per group J is 0.992 and d and g are identical for practical purposes.

Which SD if the groups differ a lot in spread?

Glass’s Δ divides by the control group’s SD instead of pooling — use it when the treatment changes variability.

Related calculators

Cohen's d Calculator

Measure effect size between two groups with Cohen’s d from their means, standard deviations and sizes — with the pooled SD and a magnitude label.

Cohen’s d Calculator (Two Samples)

Measure the standardized effect size between two groups with Cohen’s d from raw data — the mean difference in pooled standard deviation units, with a size label.

Statistical Power Calculator

Power of a two-sample test from the sample size per group, effect size and alpha — for means (Cohen’s d) or two proportions, one- or two-sided.

This calculator is for educational purposes. Double-check important results before acting on them.