Which statement best describes the difference between statistical and clinical significance?

Which statement best describes the difference between statistical and clinical significance?

• A. Statistical significance relates to p-values; clinical significance relates to meaningful effect size for patients
• B. Statistical significance relates to the sample size; clinical significance relates to patient preferences
• C. Statistical significance relates to p-values and sample size; clinical significance relates to practical importance
• D. Statistical significance relates to study design; clinical significance relates to reproducibility

Answer: (A)

The main idea is the difference between whether a result is likely due to chance and whether it matters in patient care. Statistical significance focuses on the probability that an observed difference could occur by random variation, usually assessed with a p-value. It tells you if the finding is unlikely under the null hypothesis, but it doesn’t say whether the difference is large enough to matter to patients. Clinical significance, on the other hand, asks whether the size of the effect is large enough to have real, practical importance in treatment decisions and patient outcomes. So you can have a result that’s statistically significant but with a tiny effect size that wouldn’t change clinical practice, and you can have a clinically important effect that isn’t statistically significant in a small study. The best description, then, is that statistical significance relates to p-values and the probability the finding is due to chance, while clinical significance relates to the practical importance of the effect for patients.

The main idea is the difference between whether a result is likely due to chance and whether it matters in patient care. Statistical significance focuses on the probability that an observed difference could occur by random variation, usually assessed with a p-value. It tells you if the finding is unlikely under the null hypothesis, but it doesn’t say whether the difference is large enough to matter to patients. Clinical significance, on the other hand, asks whether the size of the effect is large enough to have real, practical importance in treatment decisions and patient outcomes.

So you can have a result that’s statistically significant but with a tiny effect size that wouldn’t change clinical practice, and you can have a clinically important effect that isn’t statistically significant in a small study. The best description, then, is that statistical significance relates to p-values and the probability the finding is due to chance, while clinical significance relates to the practical importance of the effect for patients.