False Discovery Rate In Screening Calculator

Work out false discovery rate in screening instantly with clear inputs, formula shown and shareable results.

About False Discovery Rate In Screening Calculator

Applies Bayes' theorem to prevalence, sensitivity and specificity to show what share of positive screening results are false.

Formula

Predictive values

PPV = prevalence x sensitivity / (prevalence x sensitivity + (1 - prevalence) x (1 - specificity)); false discovery rate = 1 - PPV

Worked example

With the default values below, False Discovery Rate In Screening Calculator returns False discovery rate of 84.615%. Change any input above and every figure here is recalculated in your browser.

Inputs used

Disease prevalenceaccepts 0.001–60: 1
Test sensitivityaccepts 10–100: 90
Test specificityaccepts 10–100: 95

Results

False discovery rate: 84.615%
Positive predictive value: 15.385%
Negative predictive value: 99.8938%
False positives per true positive: 5.500

Step by step

1Values used
2Predictive values
3False discovery rate= 84.615
4Positive predictive value= 15.385
5Negative predictive value= 99.8938
6False positives per true positive= 5.500

Assumptions and limits

The result is derived only from the 3 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
Figures are rounded for display to 4 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Why are most positives false in rare diseases?

Even a small false positive rate applied to the large healthy majority produces more false than true positives.

How is this mitigated?

Two-stage screening: a sensitive first test followed by a highly specific confirmatory test.