Relative Risk Calculator

Relative risk (RR), also called risk ratio, compares the probability of a disease or outcome occurring in an exposed group versus a control group. It's calculated by dividing the risk in the exposed group by the risk in the control group.

An RR of 1 means equal risk in both groups. RR > 1 indicates increased risk in the exposed group, while RR < 1 suggests protective effect. For example, RR = 2 means twice the risk in the exposed group.

A confidence interval provides a range of plausible values for the true relative risk. A 95% CI means we're 95% confident the true RR lies within this range. If the CI includes 1, the result may not be statistically significant.

Relative risk compares risks (probabilities) directly, while odds ratio compares odds. RR is more intuitive but requires cohort study data. Odds ratio can be calculated from case-control studies and approximates RR when the outcome is rare.

Use relative risk for cohort studies where you follow exposed and unexposed groups over time to measure outcome occurrence. It's ideal for evaluating treatment effects, risk factors, or preventive interventions in clinical and epidemiological research.

The standard error of ln(RR) is calculated using the formula: SE = sqrt(1/a + 1/c - 1/(a+b) - 1/(c+d)), where a, b, c, d represent the four cells of the 2x2 contingency table.

When zero events occur in either group, calculations become problematic. A common approach is to add 0.5 to all four cells of the 2x2 table before calculating, though this should be interpreted cautiously.