Negative Screen Residual Risk
Update carrier risk after a negative screen using explicit prior risk, sensitivity, and specificity.
Description
A negative screen changes carrier risk according to both sensitivity and specificity.
A negative screen changes carrier risk according to both sensitivity and specificity. Missed carriers remain among the possible negative results.
Update carrier risk after a negative screen using explicit prior risk, sensitivity, and specificity.
When to use Negative Screen Residual Risk
Use this for the following task: Update carrier risk after a negative screen using explicit prior risk, sensitivity, and specificity.
Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
How to use Negative Screen Residual Risk and understand its results
- Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
- Enter priorCarrierRisk, detectionSensitivity, testSpecificity using the field table, then run the tool.
- Read residualCarrierRisk, negativeResultProbability. Interpret flags, units, ordering and placeholder values using the rules below.
- Review any reported issue or failed check, correct the supplied values when appropriate, and verify the result in its intended context.
| Input field | Meaning | Value type and bounds | Requirement |
|---|---|---|---|
| priorCarrierRisk | Prior carrier risk | number | Required |
| detectionSensitivity | Detection sensitivity | number | Required |
| testSpecificity | Test specificity | number | Required |
Supply probabilities in [0,1] and require a positive modeled negative-result probability. Apply Bayes’ rule and return both the posterior risk and negative probability.1
missed = prior(1−sensitivity); P(negative)=missed+(1−prior)specificity; residual=missed/P(negative) This summarizes the declared operation. Units, indexing, inclusivity and exceptional cases are explained in the surrounding text.
| Output field | Meaning | Value type |
|---|---|---|
| residualCarrierRisk | Residual carrier risk | number |
| negativeResultProbability | Negative result probability | number |
{
"input": {
"priorCarrierRisk": 0.1,
"detectionSensitivity": 0.9,
"testSpecificity": 1
},
"output": {
"residualCarrierRisk": 0.010989010989010986,
"negativeResultProbability": 0.91
}
}Limitations and assumptions
Assay performance and prior risk must fit the tested setting. This does not establish an individual’s carrier status.
The tool evaluates supplied observations or a declared model. It does not establish the biological cause of an observed pattern. Malformed requests produce input errors. A successfully evaluated request can still contain false flags, empty result lists or a result outside the supplied threshold; those outcomes have the meanings stated above.
Alternative or Complementary methods
Choose Two Generation Bayes Update for this operation: Apply sequential family-evidence likelihood ratios from two generations to a prior risk. For a complementary task, use Genotype Carrier Penetrance for this operation: Estimate observed penetrance among assessed carriers of a defined genotype.
The implementation reference documents the exact calculation, supported input shapes and returned fields.
References
-
Negative Screen Residual Risk — tool.io
Similar or alternative tools
- Two Generation Bayes Update
Apply sequential family-evidence likelihood ratios from two generations to a prior risk.
- Genotype Carrier Penetrance
Estimate observed penetrance among assessed carriers of a defined genotype.