What Is Effect Size?
A quantitative measure of the magnitude of a treatment effect, independent of sample size. Common metrics include Cohen's d, standardised mean difference (SMD), relative risk (RR), and odds ratio (OR).
Why It Matters for Supplement Brands
While p-values tell you whether an effect is statistically significant, effect sizes tell you how big the effect actually is. For supplement substantiation, effect size determines whether a claim is practically meaningful — a statistically significant but tiny effect may not justify a marketing claim.
How It Works
Common effect size metrics in supplement research:
1. **Cohen's d / SMD (Standardised Mean Difference)**: Measures the difference between two group means in standard deviation units. • Small: d = 0.2 • Medium: d = 0.5 • Large: d = 0.8
2. **Weighted Mean Difference (WMD)**: The actual numerical difference between groups in the original measurement units (e.g., mg/dL reduction in CRP).
3. **Relative Risk (RR)**: The ratio of event probability in the treatment vs. control group. RR = 0.75 means a 25% risk reduction.
4. **Odds Ratio (OR)**: Similar to RR but uses odds. Common in meta-analyses of binary outcomes.
5. **Number Needed to Treat (NNT)**: How many people need to take the supplement for one person to benefit. Lower = stronger effect.
When evaluating supplement studies, always look at the effect size alongside the p-value. A study can be statistically significant (p < 0.05) but have a trivially small effect size, or vice versa.
Common Mistakes to Avoid
- ✗Ignoring effect sizes and relying only on p-values to judge study importance
- ✗Not providing context for what the effect size means in practice (e.g., 'a 2 mmHg blood pressure reduction — is that clinically meaningful?')
- ✗Comparing effect sizes across studies that use different metrics (SMD vs. WMD vs. RR)
- ✗Assuming large effect sizes from single small studies are reliable — they typically shrink in larger replications
- ✗Not considering the confidence interval around the effect size — wide CIs indicate uncertainty
Related Terms
See It in Action
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