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  2. Pre- and post-test probability - Wikipedia

    en.wikipedia.org/wiki/Pre-_and_post-test_probability

    Pre-test probability and post-test probability (alternatively spelled pretest and posttest probability) are the probabilities of the presence of a condition (such as a disease) before and after a diagnostic test, respectively. Post-test probability, in turn, can be positive or negative, depending on whether the test falls out as a positive test ...

  3. Likelihood ratios in diagnostic testing - Wikipedia

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

    In evidence-based medicine, likelihood ratios are used for assessing the value of performing a diagnostic test. They use the sensitivity and specificity of the test to determine whether a test result usefully changes the probability that a condition (such as a disease state) exists. The first description of the use of likelihood ratios for ...

  4. Spearman–Brown prediction formula - Wikipedia

    en.wikipedia.org/wiki/Spearman–Brown_prediction...

    The Spearman–Brown prediction formula, also known as the Spearman–Brown prophecy formula, is a formula relating psychometric reliability to test length and used by psychometricians to predict the reliability of a test after changing the test length. [1] The method was published independently by Spearman (1910) and Brown (1910). [2][3]

  5. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  6. Bonferroni correction - Wikipedia

    en.wikipedia.org/wiki/Bonferroni_correction

    The Bonferroni correction compensates for that increase by testing each individual hypothesis at a significance level of , where is the desired overall alpha level and is the number of hypotheses. [4] For example, if a trial is testing hypotheses with a desired overall , then the Bonferroni correction would test each individual hypothesis at .

  7. Cognitive pretesting - Wikipedia

    en.wikipedia.org/wiki/Cognitive_pretesting

    Cognitive pretesting. Cognitive pretesting, or cognitive interviewing, is a field research method where data is collected on how the subject answers interview questions. It is the evaluation of a test or questionnaire before it's administered. [1] It allows survey researchers to collect feedback regarding survey responses and is used in ...

  8. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    Test statistic is a quantity derived from the sample for statistical hypothesis testing. [1] A hypothesis test is typically specified in terms of a test statistic, considered as a numerical summary of a data-set that reduces the data to one value that can be used to perform the hypothesis test. In general, a test statistic is selected or ...

  9. Kuder–Richardson formulas - Wikipedia

    en.wikipedia.org/wiki/Kuder–Richardson_formulas

    Kuder–Richardson formulas. In psychometrics, the Kuder–Richardson formulas, first published in 1937, are a measure of internal consistency reliability for measures with dichotomous choices. They were developed by Kuder and Richardson.