The ratio of a likelihood function for an unknown parameter vector to the likelihood function calculated at the estimated parameter vector. The relationship of this ratio to the chi-squared distribution can then be used to calculate confidence bounds and confidence regions.

An operator defined as the percentage of patients positive by gold standard for a particular disease, condition or injury who have a particular test result divided by the percentage of patients without the problem who have that same test result. A likelihood ratio of two means that the test result in question is twice as likely to come a patient with the problem as it is from a patient without the problem. The LR may be derived from reported sensitivity and specificity or from a clear understanding of the above definition. To see how the LR is used, see Bayes‘ Theorem; to actually use it, see the nomogram. To see how the Likelihood Ratio is generated, use the calculator

Ratio of the probability that a given diagnostic test result will be expected for a patient with the target disorder rather than for a patient without the disorder. ( Diagnosis) To Calculation

A measure of the discriminatory power of a test. The LR is the ratio of the probability of a result when the condition under consideration is true to the probability of a result when the condition under consideration is false (for example, the probability of a result in a diseased patient to the probability of a result in a nondiseased patient). The LR for a positive test is the ratio of true-positive rate (TPR) to false-positive rate (FPR).

The ratio of the probability of a test result among patients with the target disorder to the probability of that same test result among patients who are free of the target disorder. The LR for a positive test (positive likelihood ratio) is calculated as sensitivity/ ( 1-specificity). The LR for a negative test (negative likelihood ratio) is calculated as (1-sensitivity)/specificity.

The ratio of two probabilities of the same event under different hypotheses. In DNA testing often expressed as the ratio between the likelihood that a given profile came from a particular individual and the likelihood that it came from a random unrelated person. Note that in this case the likelihood of each event does not add to give 1 (100% likelihood) as it does not incorporate the possibility of error or that the profiles came from twins or other near relatives.

a way of summarising the findings of a study of a diagnostic test for use in clinical situations where there may be differences in the prevalence of the disease. The likelihood ratio for a positive test is the likelihood that a positive test result comes from a person that really does have the disorder rather than one that does not have the disorder [sensitivity/(1-specificity)]. The likelihood ratio for a negative test is the likelihood that a negative test result comes from a person with the disorder rather than one without the disorder [(1-sensitivity)/specificity].

a statistical term that measures the value of a piece of evidence. Equal to the probability of seeing a piece of evidence given the prosecutor's hypothesis, divided by probability of seeing a piece of evidence given the defence hypothesis.

For a screening or diagnostic test (including clinical signs or symptoms), expresses the relative odds that a given test result would be expected in a patient with (as opposed to one without) a disorder of interest.

In diagnostic testing, the ratio of true-positives to false-positives.

is the likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without that disorder. See also Calculating Sensitivity and Specificity and on samples of Likelihood Ratios.