Relative Risk with 95% Confidence Intervals


The following is a 2 by 2 webulator used to compute relative risk . Enter the data in the cells for the appropriate rows and columns (the green coloured cells), then click on the button labelled Compute to compute the relative risk .

+ve condition (CASES) -ve condition (CONTROLS) Numerator (a/(a+b))
+ve condition (CASES) -ve condition (CONTROLS) Denominator (c/(c+d))
Not Exposed
Column Totals =
Relative Risk =
(a/(a+b)) / (c/(c+d))
ln Relative Risk

Standard Error of lnRR
95%CI lnRR lower limit
95%CI lnRR upper limit
Exponentiating the 95% Confidence Interval's Upper and Lower limits will return the estimated values to the original scale scores lower limit of 95%CI
Relative Risk
upper limit of 95%CI
Relative Risk

The relative risk estimate suggests that:
The condition (or outcome) is RR times more likely to occur among those individuals that are exposed to the suspected risk factor (related to) THAN among those individuals with no exposure to the risk factor (unrelated to).

As a rule, the larger the value of the relative risk, that is greater than 1, the stronger the association between the disease or disorder of interest and exposure to the risk factor.

Likewise, values of the relative risk estimate that are close to 1 indicate that the disease and exposure to the risk factor are unrelated (i.e., the risk of occurrence is the same for both exposed and non-exposed individuals).

Similarly values of RR less than 1 indicate a negative association between the risk factor and the disease. A relative risk estimate less than 1 is said to demonstrate a protective effect rather than a detrimental effect.

Click here to return to the Webulator Menu Page

For more information, please contact:

Professor William J. Montelpare, Ph.D.,
Margaret and Wallace McCain Chair in Human Development and Health,
Department of Applied Human Sciences, Faculty of Science,
Health Sciences Building, University of Prince Edward Island,
550 Charlottetown, PE, Canada, C1A 4P3
(o) 902 620 5186

Visiting Professor, School of Healthcare, University of Leeds,
Leeds, UK, LS2 9JT
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