likelihood ratio

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likelihood ratio

usually preceded by "maximum" (that is, maximum likelihood ratio), this ratio maximizes the probability that the parameters in the ratio agree with the empirically observed data.

like·li·hood ra·ti·o

(līk'lē-hud rā'shē-ō)
The ratio of the probability of a test result among patients with a certain disease or disorder to the probability of that same test result among patients who do not have the targeted disease or disorder.

likelihood ratio

(līk′lē-hood″),

LR

A statistical tool used to help determine the usefulness of a diagnostic test for including or excluding a particular disease. An LR = 1 suggests that the test ordered neither helps to diagnose the disease in question nor helps to rule it out. Higher LRs increase the probability that the disease will be present; LRs < 1.0 decrease the probability that the disease is present.

A positive LR can be thought of as the probability that someone with a suspected condition will, accurately, have a positive test result, divided by the probability that a healthy person will, inaccurately, test positive for the disease. Mathematically this can be represented by the following equation: LR+ = sensitivity of the test/ (1− specificity of the test). A negative LR is the probability that a sick person will fail to be detected by the test, divided by the probability that a healthy person will be accurately shown by the test to have no sign of disease. Mathematically: LR− = (1 − sensitivity of the test) / specificity of the test.

likelihood ratio

The percentage of ill people with a given test result divided by the percentage of well people with the same result. Ratios near unity should not influence decisions. This useful guide to refining clinical diagnosis is little used mainly because of its complexity; The Fagan nomogram can simplify the matter.
References in periodicals archive ?
Kim and Yoon (2011) compared multiple-group categorical CFA (MG-CFA) to the likelihood-ratio test in IRT in detecting measurement invariance in simulating data.
The likelihood-ratio test in all cases rejects the null hypothesis of no overdispersion (p value = .
Most likely position, likelihood-ratio test statistic values, and estimated effects of QTL for six growth and carcass quality traits in Hanwoo steers Trait cM (a) LRT (b) Average daily gain 35 4.
Likelihood-ratio tests were therefore carried out to determine whether the model allowing [beta] to vary freely yielded significantly better fits than one with three parameters and [beta] fixed at 3.
We, therefore, developed likelihood-ratio test for log-log unit slope when the variance is not proportional to the squared mean.
As each new set of parameters was added, a likelihood-ratio test was performed to determine whether the simpler model could be rejected (Goldman 1993; Yang 1996b).
Obviously, the likelihood-ratio test does not call for constrained ML estimation.
We tested the first hypothesis, that host and parasite topologies are in complete agreement and sampling error has produced different trees, by using the likelihood-ratio test for identical topology.
That is, likelihood-ratio tests (LRTs) used for model selection and hypotheses testing are the difference between the log-likelihood statistics for goodness of fit of the models being compared if the models are nested.
In this case, a measure is needed of the average selection pattern of the group, where data from each individual are weighted equally instead of weighting according to the number of observations as is done by the likelihood-ratio test.
A likelihood-ratio test for this model against the null hypothesis of no selection on either trait (i.