Positive Predictive Value Calculator

Enter the number of true positives (a), false negatives (b), false positives (c), and true negatives (d) from your diagnostic test results — the Positive Predictive Value Calculator computes PPV, NPV, Sensitivity, Specificity, and likelihood ratios. You can also override with a known disease prevalence to get adjusted predictive values that reflect real-world conditions.

Number of patients who have the disease AND tested positive.

Number of patients who have the disease but tested negative.

Number of patients who do not have the disease but tested positive.

Number of patients who do not have the disease AND tested negative.

%

If your sample does not reflect real-world prevalence, enter the actual disease prevalence (%) here to adjust PPV and NPV.

Results

Positive Predictive Value (PPV)

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Negative Predictive Value (NPV)

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Sensitivity

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Specificity

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Positive Likelihood Ratio (LR+)

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Negative Likelihood Ratio (LR−)

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Prevalence Used

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PPV vs NPV Breakdown

Results Table

Frequently Asked Questions

What is Positive Predictive Value (PPV)?

Positive Predictive Value (PPV) is the probability that a patient who tests positive actually has the disease. It is calculated as true positives divided by all positive test results (true positives + false positives). A higher PPV means fewer false alarms from a positive result.

How does disease prevalence affect PPV?

PPV is strongly influenced by disease prevalence. Even a highly sensitive and specific test will produce many false positives — and a low PPV — when applied to a population where the disease is rare. As prevalence increases, PPV rises because true positives become more common relative to false positives.

What is the difference between sensitivity and PPV?

Sensitivity measures how well a test identifies people who truly have the disease (true positive rate), and is a fixed property of the test itself. PPV, on the other hand, reflects how likely a positive result is to be correct in a specific population, and changes depending on disease prevalence.

What is Negative Predictive Value (NPV)?

NPV is the probability that a patient who tests negative truly does not have the disease. It is calculated as true negatives divided by all negative test results. Like PPV, NPV is affected by disease prevalence — NPV tends to be high when prevalence is low.

What are Likelihood Ratios (LR+ and LR−)?

The Positive Likelihood Ratio (LR+) indicates how much more likely a positive test result is in someone with the disease compared to someone without it. The Negative Likelihood Ratio (LR−) shows how much less likely a negative result is in someone with the disease. LR+ > 10 and LR− < 0.1 are generally considered strong diagnostic indicators.

When should I use the prevalence override field?

Use the prevalence override when your study sample was artificially constructed (e.g., equal numbers of diseased and non-diseased patients) and does not reflect the real-world frequency of the disease. Entering the true population prevalence allows the calculator to adjust PPV and NPV to values that are clinically meaningful.

What formula is used to calculate PPV?

The formula is: PPV = (Sensitivity × Prevalence) / [(Sensitivity × Prevalence) + (1 − Specificity) × (1 − Prevalence)]. When no prevalence override is provided, prevalence is estimated directly from the sample as (a + b) / (a + b + c + d).

Can this calculator be used for any diagnostic test?

Yes — this calculator applies to any binary diagnostic test where outcomes can be classified as true positive, false negative, false positive, or true negative. It is widely used in clinical medicine, genetics screening, epidemiology, and machine learning model evaluation.

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