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  2. Likelihood ratios in diagnostic testing - Wikipedia

    en.wikipedia.org/wiki/Likelihood_ratios_in...

    Likelihood Ratio: An example "test" is that the physical exam finding of bulging flanks has a positive likelihood ratio of 2.0 for ascites. Estimated change in probability: Based on table above, a likelihood ratio of 2.0 corresponds to an approximately +15% increase in probability.

  3. Likelihood-ratio test - Wikipedia

    en.wikipedia.org/wiki/Likelihood-ratio_test

    In statistics, the likelihood-ratio test is a hypothesis test that involves comparing the goodness of fit of two competing statistical models, typically one found by maximization over the entire parameter space and another found after imposing some constraint, based on the ratio of their likelihoods.

  4. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    The likelihood ratio is central to likelihoodist statistics: the law of likelihood states that the degree to which data (considered as evidence) supports one parameter value versus another is measured by the likelihood ratio. In frequentist inference, the likelihood ratio is the basis for a test statistic, the so-called likelihood-ratio test.

  5. Likelihood principle - Wikipedia

    en.wikipedia.org/wiki/Likelihood_principle

    In Bayesian statistics, this ratio is known as the Bayes factor, and Bayes' rule can be seen as the application of the law of likelihood to inference. In frequentist inference , the likelihood ratio is used in the likelihood-ratio test , but other non-likelihood tests are used as well.

  6. Neyman–Pearson lemma - Wikipedia

    en.wikipedia.org/wiki/Neyman–Pearson_lemma

    In practice, the likelihood ratio is often used directly to construct tests — see likelihood-ratio test.However it can also be used to suggest particular test-statistics that might be of interest or to suggest simplified tests — for this, one considers algebraic manipulation of the ratio to see if there are key statistics in it related to the size of the ratio (i.e. whether a large ...

  7. G-test - Wikipedia

    en.wikipedia.org/wiki/G-test

    We can derive the value of the G-test from the log-likelihood ratio test where the underlying model is a multinomial model.. Suppose we had a sample = (, …,) where each is the number of times that an object of type was observed.

  8. Uniformly most powerful test - Wikipedia

    en.wikipedia.org/wiki/Uniformly_most_powerful_test

    In statistical hypothesis testing, a uniformly most powerful (UMP) test is a hypothesis test which has the greatest power among all possible tests of a given size α.For example, according to the Neyman–Pearson lemma, the likelihood-ratio test is UMP for testing simple (point) hypotheses.

  9. Monotone likelihood ratio - Wikipedia

    en.wikipedia.org/wiki/Monotone_likelihood_ratio

    In statistics, the monotone likelihood ratio property is a property of the ratio of two probability density functions (PDFs). Formally, ... Example: Let be an input ...