Post-Test Probability Calculator
Estimate how a diagnostic test result changes disease probability. Enter the pre-test probability and test performance to instantly view the positive and negative post-test probabilities.
Post-test P (Positive)
66.67%
Probability disease is present after a positive result
Post-test P (Negative)
1.16%
Probability disease is present after a negative result
LR+
18.00
Factor applied to odds after a positive test
LR−
0.11
Factor applied to odds after a negative test
How to Use This Calculator
- Estimate pre-test probability from prevalence data or clinical judgement.
- Choose whether you know the test’s sensitivity/specificity or likelihood ratios.
- Enter the appropriate values to compute post-test probabilities instantly.
- Review the interpretation panel to understand the diagnostic impact.
Formulas
Pre-test odds = Ppre / (1 − Ppre)
Post-test odds (positive) = Pre-test odds × LR+
Post-test odds (negative) = Pre-test odds × LR−
Post-test probability = Odds / (1 + Odds)
LR+ = Sensitivity / (1 − Specificity)
LR− = (1 − Sensitivity) / Specificity
Likelihood ratios summarize how much more (or less) likely a given test result is in patients with the condition versus those without it. Combining pre-test probability with LR values yields a post-test probability using Bayes' theorem in odds form.
Frequently Asked Questions
How accurate are the results?
The calculator applies standard formulas for diagnostic testing and is as accurate as the inputs provided. Always consider measurement error and real-world variability when interpreting outputs.
What if sensitivity or specificity equals 1?
Perfect tests are rare. Values are gently clamped below 1 to avoid division by zero, approximating ideal behavior while keeping calculations stable.
Can likelihood ratios be less than 1?
Yes. LR+ is usually > 1 and LR− is usually < 1. Ratios near 1 indicate minimal diagnostic information provided by the test.
How should I estimate pre-test probability?
Use epidemiologic prevalence data, clinical scoring tools, or expert judgement. The quality of the pre-test estimate heavily influences the usefulness of the post-test result.