What is the positive likelihood ratio (LR+)?

LR+ = Sensitivity / (1 − Specificity). It quantifies how much more likely a positive test result is in someone who has the disease versus someone who does not. LR+ > 10 is generally considered strong evidence for disease.

What is the negative likelihood ratio (LR−)?

LR− = (1 − Sensitivity) / Specificity. It quantifies how much more likely a negative test result is in a diseased person compared to a healthy one. LR− < 0.1 is generally considered strong evidence against disease.

How do I convert pre-test probability to post-test probability?

Convert pre-test probability to odds: pre-test odds = p / (1 − p). Multiply by the LR: post-test odds = pre-test odds × LR. Convert back: post-test probability = post-test odds / (1 + post-test odds). This calculator does all steps automatically.

What are "good" likelihood ratio values?

Rule of thumb: LR+ > 10 or LR− < 0.1 provides large, often conclusive shifts in probability. LR+ 5–10 or LR− 0.1–0.2 provides moderate shifts. LR close to 1 means the test adds little diagnostic value.

Why are likelihood ratios better than sensitivity/specificity alone?

Sensitivity and specificity are population-level test properties. Likelihood ratios let you directly update a specific patient's pre-test probability into a post-test probability, making clinical reasoning explicit and reproducible.

Can I use this for machine-learning classifiers?

Yes. For a binary classifier, sensitivity = recall and specificity = 1 − FPR. Enter these values to get LR+ and LR−, which measure how much a positive or negative prediction shifts the prior probability of a true positive.

Likelihood Ratio Calculator

Name: Likelihood Ratio Calculator
Availability: InStock
Author: Nham Vu

Enter sensitivity and specificity to get LR+ and LR−, then convert a pre-test probability to a post-test probability using Bayes theorem.

Test Performance

Enter the diagnostic test's sensitivity and specificity.

Sensitivity (%) — true positive rate

Specificity (%) — true negative rate

Pre-test Probability (%) — optional, for post-test calc

Disease prevalence in the tested population, or your clinical prior.

Enter sensitivity and specificity, then click Calculate.

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Summary

Enter sensitivity and specificity to get LR+ and LR−, then convert a pre-test probability to a post-test probability using Bayes theorem.

How it works

Enter the sensitivity (true positive rate) as a percentage.
Enter the specificity (true negative rate) as a percentage.
LR+ is computed as Sensitivity / (1 − Specificity).
LR− is computed as (1 − Sensitivity) / Specificity.
Optionally enter a pre-test probability to calculate the post-test probability using the odds form of Bayes theorem: post-test odds = LR × pre-test odds.
Post-test probability is converted back from odds: probability = odds / (1 + odds).

Use cases

Evaluate how much a positive or negative diagnostic test result shifts disease probability.
Compare the discriminating power of two competing diagnostic tests.
Calculate post-test probability for a clinical decision at the bedside.
Validate a machine-learning binary classifier beyond raw accuracy.
Teaching evidence-based medicine concepts in a clinical setting.
Determine whether a screening test result meaningfully changes management.

Frequently Asked Questions

Last updated: 2026-06-11 · Reviewed by Nham Vu