What is Positive Predictive Value (PPV)?

PPV is the probability that a person with a positive test result truly has the disease. It equals TP / (TP + FP). PPV depends heavily on disease prevalence — even a highly accurate test has low PPV in a low-prevalence population.

What is Negative Predictive Value (NPV)?

NPV is the probability that a person with a negative test result truly does not have the disease. It equals TN / (TN + FN). High NPV is critical for ruling-out diseases.

How do sensitivity and specificity differ from PPV and NPV?

Sensitivity (true positive rate) and specificity (true negative rate) are intrinsic test properties that do not change with prevalence. PPV and NPV are prevalence-dependent — they describe the value of the test result in a specific population.

What are likelihood ratios and why are they useful?

The positive likelihood ratio (LR+) equals sensitivity / (1 − specificity). The negative likelihood ratio (LR−) equals (1 − sensitivity) / specificity. They are prevalence-independent and allow Bayesian updating of pre-test to post-test probability using Fagan nomograms.

Why does PPV change with disease prevalence?

In a rare disease, even a small false-positive rate generates many false positives relative to the few true positives, driving PPV down. For the same test, PPV is much higher in a high-prevalence population.

What is diagnostic accuracy (overall accuracy)?

Overall accuracy = (TP + TN) / (TP + FP + FN + TN). It represents the proportion of all tests that gave the correct result. It can be misleading in imbalanced datasets and should be interpreted alongside PPV, NPV, sensitivity, and specificity.

Positive Predictive Value Epi

Enter your 2x2 contingency table values to instantly compute PPV, NPV, sensitivity, specificity, and likelihood ratios for diagnostic test evaluation.

2×2 Contingency Table

Enter raw cell counts from your diagnostic study.

Disease +

Disease −

Test +

Test −

TP — True Positives: disease+ & test+

FP — False Positives: disease− & test+

FN — False Negatives: disease+ & test−

TN — True Negatives: disease− & test−

Enter values and click Calculate to see results.

Predictive Values

PPV

—

Positive Predictive Value

NPV

—

Negative Predictive Value

Test Performance

Sensitivity

—

True Pos. Rate

Specificity

—

True Neg. Rate

Accuracy

—

Overall

Likelihood Ratios

LR+

—

Positive LR

LR−

—

Negative LR

LR+ > 10 strongly rules in; LR− < 0.1 strongly rules out.

Population Summary

Total N —

Prevalence —

Disease + —

Disease − —

Test + —

Test − —

Summary

This tool computes all standard metrics from a 2x2 diagnostic contingency table: PPV, NPV, sensitivity, specificity, overall accuracy, and both likelihood ratios. Enter the four cell counts (TP, FP, FN, TN) and results appear instantly. All formulas follow standard epidemiological definitions and the results include a prevalence estimate derived from your input data.

How it works

Fill in the four cells of the 2x2 table: True Positives, False Positives, False Negatives, True Negatives.
The tool calculates totals for disease-positive, disease-negative, test-positive, and test-negative groups.
Sensitivity = TP / (TP + FN); Specificity = TN / (TN + FP).
PPV = TP / (TP + FP); NPV = TN / (TN + FN).
LR+ = Sensitivity / (1 − Specificity); LR− = (1 − Sensitivity) / Specificity.
Prevalence and overall accuracy are computed from the full table totals.

Use cases

Evaluate a screening test before clinical adoption.
Compare the accuracy of two competing diagnostic assays.
Calculate observed PPV and NPV directly from prospective cohort screening study counts.
Teach epidemiology students the relationship between prevalence and PPV.
Assess a rapid antigen test vs. a reference PCR standard.
Determine whether a high-specificity or high-sensitivity test is appropriate.
Audit published diagnostic studies for reported accuracy metrics.
Evaluate point estimates of diagnostic performance metrics from completed or pilot study data.

Frequently Asked Questions

Last updated: 2026-06-18 · Reviewed by Nham Vu