Courtesy of Tris Pharma Medical Affairs.

This site is intended for U.S. healthcare professionals only.

Biostatistics What is an effect size, and how is it interpreted?72 What is an effect size, and how is it interpreted?72

Effect size is a measure of the difference between interventions in clinical studies

Examples of absolute effect size include Cohen's d, area under the curve, success rate difference, attributable risk, and number needed to treat/harm (NNT/NNH)

Each measure describes effect size in a different way

Effect size is a way to convey the clinical relevance, or clinical significance, of clinical study results

An observed difference in outcomes must translate to a meaningful clinical difference in real-world practice in order to be relevant to patients and clinicians

Effect size is a measure of the difference between interventions in clinical studies

Examples of absolute effect size include Cohen's d, area under the curve, success rate difference, attributable risk, and number needed to treat/harm (NNT/NNH)

Each measure describes effect size in a different way

Effect size is a way to convey the clinical relevance, or clinical significance, of clinical study results

An observed difference in outcomes must translate to a meaningful clinical difference in real-world practice in order to be relevant to patients and clinicians

References

72. Citrome L, Ketter TA. When does a difference make a difference? Interpretation of number needed to treat, number needed to harm, and likelihood to be helped or harmed. Int J Clin Pract. 2013;67(5):407–411.