Glossary · Methodology
Confidence interval
In short
The confidence interval is the range in which the true value of a study result plausibly lies, usually given as a 95 percent interval. The narrower it is, the more precise the estimate.
A study never measures the whole population, only a sample. The result is therefore an estimate with some blur. The interval makes this blur visible: a hazard ratio of 0.80 with an interval of 0.70 to 0.90 is a very different statement from 0.80 with 0.40 to 1.60.
If the interval includes the value that means “no difference” — 1 for ratios, 0 for differences — the result is not statistically significant. That does not mean there is no effect, but that the data do not clearly show one.
Strictly speaking, the 95 percent interval describes a procedure: if the study were repeated very many times, about 95 out of 100 intervals calculated this way would contain the true value.
Every study number has some blur — the interval shows how much.
Where this comes up in the fact checks
- Aspirin for prevention – Hazard ratio 1.01 with an interval of 0.92 to 1.11: a large benefit is hardly compatible with this narrow interval.
- HMB – The gain in muscle mass was just at the threshold of significance — so the interval reaches close to zero.
Sources
Related terms: Statistical significance (p-value) · Hazard ratio · Effect size
Information only, not medical advice. The BK-Score is a subjective assessment according to disclosed rules – not a scientific evaluation. Scoring rules