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Post-Test Probability Calculator — result sheet
Use prevalence, sensitivity, and specificity to estimate positive and negative post-test probabilities with Bayes' theorem.
Inputs used
Results
Visual chart
Breakdown
Calculation steps
Returned data table
Formula and methodology
Formula: PPV = prevalence×sensitivity ÷ [prevalence×sensitivity + (1−prevalence)×(1−specificity)]; NPV uses the corresponding negative-result pathways.
A test's sensitivity and specificity do not by themselves answer how likely a condition is after a result. This calculator combines them with a stated pre-test prevalence and shows positive and negative post-test probabilities, including the false-result shares that shape the denominator.
This result follows the calculator's declared inputs, precision, validation boundaries, and model limits.
Input contract
- Pre-test prevalence — %; minimum 0; maximum 100
- Sensitivity — %; minimum 0; maximum 100
- Specificity — %; minimum 0; maximum 100
Worked example
| Input | Value |
|---|---|
| Pre-test prevalence | 3 |
| Sensitivity | 80 |
| Specificity | 95 |
Positive post-test probability is about 33.1034%; negative post-test probability of no condition is about 99.3531%.
Assumptions and limits
- Prevalence, sensitivity, and specificity describe the same population, test, and decision threshold.
- The positive and negative pathways are treated as conditional probabilities for a binary condition and binary test result.
- The result is a mathematical Bayes model and does not diagnose an individual or replace a clinician's interpretation.
- Selection bias, verification bias, changing prevalence, test indeterminates, and dependence between tests are not modeled.
Calculator note
Source and methodology
Use the official WorldCalculate methodology policy for the source, formula, precision, and boundary standards behind this calculator.
Planning estimate, not financial, medical, legal, or professional advice. © WorldCalculate — reuse with attribution. Built and curated by Hassan ALRowaie.
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