negative predictive value

USAGE SUMMARY

"negative predictive value" is correct and usable in written English. You can use it in contexts related to statistics, medical testing, or diagnostic accuracy. For example: "The negative predictive value of the test indicates how likely it is that a negative result is accurate." Alternative expressions include "NPV" and "negative predictive accuracy."

✓ Grammatically correct

Science

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The negative predictive value was 82%.

Stanford University

The negative predictive value was >99%.

American Journal of Obstetrics and Gynecology

Specificity and negative predictive value were unchanged.

European Journal of Vascular and Endovascular Surgery

NPV: negative predictive value.

Clinical and Translational Medicine

Negative predictive value = 40.6%.

International Journal of Emergency Medicine

Negative predictive value.

Insights into Imaging

The negative predictive value was 50%.

Duke University

Negative predictive value achieved about 98% [1].

Critical Ultrasound Journal

The negative predictive value was only 58%.

Annals of Intensive Care

NPV: Negative predictive value in percentage.

International Journal of Emergency Medicine

Negative predictive value = d / (c + d).

Journal of Ophthalmic Inflammation and Infection

Expert writing Tips

Best practice

Clearly define the population and testing conditions when stating the "negative predictive value" to ensure the results are interpreted correctly in the appropriate context.

Common error

Avoid interchanging "negative predictive value" with positive predictive value. NPV focuses on the probability of the absence of disease when the test is negative, whereas PPV focuses on the probability of the presence of disease when the test is positive.

Linguistic Context

The phrase "negative predictive value" functions as a noun phrase, typically used in statistical and medical contexts. Ludwig examples show it's employed to quantify the reliability of a negative test result in correctly identifying the absence of a condition.

Expression frequency: Very common

Frequent in

Science

88%

Academia

12%

News & Media

0%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, the phrase "negative predictive value" is a grammatically sound noun phrase predominantly utilized within scientific and academic spheres. As Ludwig AI indicates, its primary function is to quantify the reliability of a negative test result, offering a measure of confidence in ruling out specific conditions. High usage consistency and the abundance of examples from credible sources reinforce its accuracy and relevance in professional and technical contexts.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

NPV

This is the abbreviation for "negative predictive value".

predictive value of a negative test

Focuses on the test rather than the value itself, but still measures the same thing.

likelihood of absence of disease given a negative test result

This is a more descriptive way of expressing the concept.

probability of no disease when the test is negative

Rephrases the concept using basic probability terms.

chance of a true negative result

Emphasizes the 'true negative' aspect.

confidence in a negative diagnosis

Focuses on the confidence level associated with a negative result.

reliability of a negative prediction

Highlights the reliability aspect.

accuracy of ruling out a condition

Emphasizes the ability to exclude a condition when the test is negative.

test's ability to correctly identify the absence of disease

Focuses on test performance in identifying the absence of disease.

effectiveness of a test at excluding a condition

Describes how well the test excludes a specific condition.

FAQs

How is "negative predictive value" calculated?

The "negative predictive value" (NPV) is calculated as: True Negatives / (True Negatives + False Negatives). It represents the probability that a person who tests negative truly does not have the disease.

What does a high "negative predictive value" mean?

A high "negative predictive value" indicates that if a test result is negative, there is a high probability that the individual truly does not have the condition being tested for. This is especially important in screening tests where the goal is to rule out disease.

How does prevalence affect the "negative predictive value"?

The prevalence of a condition significantly impacts the "negative predictive value". As prevalence decreases, the NPV generally increases, because there are fewer true positives and more true negatives in the population.

What is the difference between sensitivity, specificity, and "negative predictive value"?

Sensitivity measures the ability of a test to correctly identify those with the disease (true positives), specificity measures the ability of the test to correctly identify those without the disease (true negatives), and the "negative predictive value" measures the probability that a person with a negative test result truly does not have the disease. They are related but distinct measures of a test's accuracy.