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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 ...
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 ...
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.
Predicted reliability, ′, is estimated as: ′ = ′ + ′ where n is the number of "tests" combined (see below) and ′ is the reliability of the current "test". The formula predicts the reliability of a new test composed by replicating the current test n times (or, equivalently, creating a test with n parallel forms of the current exam).
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 .
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 ...
Computations or tables of the Wilks' distribution for higher dimensions are not readily available and one usually resorts to approximations. One approximation is attributed to M. S. Bartlett and works for large m [2] allows Wilks' lambda to be approximated with a chi-squared distribution
The Brown–Forsythe test is a statistical test for the equality of group variances based on performing an Analysis of Variance (ANOVA) on a transformation of the response variable. When a one-way ANOVA is performed, samples are assumed to have been drawn from distributions with equal variance. If this assumption is not valid, the resulting F ...