Compute odds ratio, relative risk, absolute risk reduction, and NNT from a 2×2 table. Study-design-aware with OR≠RR warnings. Data never leaves your browser.
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Enter events and non-events for exposed (treatment) and unexposed (control) groups.
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When the event rate exceeds 10%, the odds ratio substantially overestimates the relative risk. A common mistake is interpreting OR as if it were RR. Always check the event rate and report the appropriate measure for your study design.
Case-control designs sample on outcome, not exposure, so you cannot estimate true incidence rates. Only the odds ratio is valid. Reporting RR from a case-control study is a fundamental methodological error.
When the absolute risk reduction CI crosses zero, the NNT CI passes through infinity — meaning the treatment might have no effect or even cause harm. Report the full CI including the direction change (NNT to NNH).
A zero cell makes OR or RR undefined. Adding 0.5 to all four cells (Haldane-Anscombe correction) produces finite estimates with valid confidence intervals. This is standard practice in meta-analysis.
OR is computed as (a×d)/(b×c) with log-scale normal approximation CIs. RR uses risk ratios with log-scale CIs. ARR is the difference of proportions with normal approximation CIs. NNT = 1/|ARR| with CI bounds derived from ARR CI inversion. The Haldane-Anscombe correction (0.5 added to all cells) is applied when any cell is zero. Study design selection gates which measures are displayed. All calculations run client-side in the browser.
Last validated 2026-04-05. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.
ConductScience OR/RR/NNT Calculator (v1.0). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/or-rr-nnt-calculator
Altman DG. Confidence intervals for the number needed to treat. BMJ. 1998;317(7168):1309-1312. doi:10.1136/bmj.317.7168.1309
Effect measures quantify the strength and direction of an association between exposure and outcome:
• OR = (a×d)/(b×c) — odds of event in exposed vs unexposed • RR = risk_exposed / risk_unexposed — probability ratio • ARR = risk_exposed − risk_unexposed — absolute difference • RRR = ARR / risk_unexposed — proportional reduction • NNT = 1 / |ARR| — patients to treat for one benefit/harm
OR and RR measure relative effects (how many times more/less likely). ARR and NNT measure absolute effects (how much difference in practice). Both perspectives are needed for clinical decision-making.
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