# Positive and negative predictive values

**positive predictive valuenegative predictive valuepositiveNPVclinical predictive valuenegative values resultsPositive predictive valuespositive predictorprecision ratepredictive value of positive values results**

The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively.wikipedia

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### Precision and recall

**precisionrecallF-measure**

In information retrieval, the PPV statistic is often called the precision.

In pattern recognition, information retrieval and classification (machine learning), precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances, while recall (also known as sensitivity) is the fraction of the total amount of relevant instances that were actually retrieved.

### Prevalence

**lifetime prevalenceprevalence ratemorbidity rate**

The PPV and NPV are not intrinsic to the test; they depend also on the prevalence. In case-control studies the PPV has to be computed from sensitivity, specificity, but also including the prevalence: Note that the positive and negative predictive values can only be estimated using data from a cross-sectional study or other population-based study in which valid prevalence estimates may be obtained.

Even assuming that lay interview diagnoses are highly accurate in terms of sensitivity and specificity and their corresponding area under the ROC curve (that is, AUC, or area under the receiver operating characteristic curve), a condition with a relatively low prevalence or base-rate is bound to yield high false positive rates, which exceed false negative rates; in such a circumstance a limited positive predictive value, PPV, yields high false positive rates even in presence of a specificity which is very close to 100%.

### Sensitivity and specificity

**sensitivityspecificitysensitive**

In case-control studies the PPV has to be computed from sensitivity, specificity, but also including the prevalence:

Sensitivity is not the same as the precision or positive predictive value (ratio of true positives to combined true and false positives), which is as much a statement about the proportion of actual positives in the population being tested as it is about the test.

### Pre- and post-test probability

**post-test probabilitypre-test probabilitypost-test**

Although sometimes used synonymously, a positive predictive value generally refers to what is established by control groups, while a post-test probability refers to a probability for an individual.

Also, in this case, the positive post-test probability (the probability of having the target condition if the test falls out positive), is numerically equal to the positive predictive value, and the negative post-test probability (the probability of not having the target condition if the test falls out negative) is numerically complementary to the negative predictive value ( negative post-test probability = 1 - negative predictive value ), again assuming that the individual being tested does not have any other risk factors that result in that individual having a different pre-test probability than the reference group used to establish the positive and negative predictive values of the test.

### False discovery rate

**false discovery rate (FDR)positive false discovery rateBenjamini-Hochberg procedure**

The complement of the PPV is the false discovery rate (FDR):

* Positive predictive value

### Binary classification

**binary classifierbinarybinary categorization**

The row ratios are Positive Predictive Value (PPV, aka precision) (TP/(TP+FP)), with complement the False Discovery Rate (FDR) (FP/(TP+FP)); and Negative Predictive Value (NPV) (TN/(TN+FN)), with complement the False Omission Rate (FOR) (FN/(TN+FN)).

### Diagnostic odds ratio

It may also be expressed in terms of the Positive predictive value (PPV) and Negative predictive value (NPV):

### Statistics

**statisticalstatistical analysisstatistician**

The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively.

### Medical test

**diagnostic testdiagnostic testsdiagnostic testing**

The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively.

### Bayes' theorem

**Bayes' ruleBayes theoremBayes's theorem**

The PPV can be derived using Bayes' theorem.

### Information retrieval

**queryretrievalqueries**

In information retrieval, the PPV statistic is often called the precision.

### False positives and false negatives

**false positivefalse negativefalse positives**

The positive and negative predictive values (PPV and NPV respectively) are the proportions of positive and negative results in statistics and diagnostic tests that are true positive and true negative results, respectively.

### Cross-sectional study

**cross-sectionalcross-sectional studiescross-sectional analysis**

Note that the positive and negative predictive values can only be estimated using data from a cross-sectional study or other population-based study in which valid prevalence estimates may be obtained.

### Case–control study

**case-control studiescase-controlcase-control study**

In case-control studies the PPV has to be computed from sensitivity, specificity, but also including the prevalence:

### Fecal occult blood

**fecal occult blood testoccult bleedingFecal Immunochemical Test**

Suppose the fecal occult blood (FOB) screen test is used in 2030 people to look for bowel cancer:

### Likelihood ratios in diagnostic testing

**likelihood ratiolikelihood ratioslikelihood**

Otherwise, positive and negative likelihood ratios are more accurate than NPV and PPV, because likelihood ratios do not depend on prevalence.

### Relevance (information retrieval)

**relevancerelevantrelevancy ranking**

### Sensitivity index

**sensitivity index ''ddd '' (d prime)**

### Evaluation of binary classifiers

**accuracymeasure of the effectiveness**

In addition to sensitivity and specificity, the performance of a binary classification test can be measured with positive predictive value (PPV), also known as precision, and negative predictive value (NPV).

### Myocardial infarction

**heart attackheart attacksacute myocardial infarction**

Levine's sign, in which a person localizes the chest pain by clenching one or both fists over their sternum, has classically been thought to be predictive of cardiac chest pain, although a prospective observational study showed it had a poor positive predictive value.

### Hodgkin lymphoma

**Hodgkin's lymphomaHodgkin's diseaseHodgkin disease**

### Clostridioides difficile infection

**Clostridium difficileClostridium difficile'' colitisClostridium difficile'' infection**

In this study with a prevalence of positive cytotoxin assays of 14%, the positive predictive value was 18% and the negative predictive value was 94%.

### Cancer screening

**screeningcancer screeningsdetection**

### Contraction stress test

**Oxytocin challenge test**

The CST is used for its high negative predictive value.