
doi: 10.2307/2530508
pmid: 7370371
It is often required to evaluate the accuracy of a new diagnostic test against a standard test with unknown error rates. If the two tests are applied simultaneously to the same individuals from two populations with different disease prevalences, then assuming conditional independence of the errors of the two tests, the error rates of both tests and the true prevalences in both populations can be estimated by a maximum likelihood procedure. Generalizations to several tests applied in several populations are also possible.
observer agreement, Clinical Laboratory Techniques, misclassification, sensitivity, estimating error rates of diagnostic tests, Applications of statistics to biology and medical sciences; meta analysis, conditional independence of errors, Humans, Diagnostic Errors, Tuberculosis, Pulmonary, Probability, Skin Tests
observer agreement, Clinical Laboratory Techniques, misclassification, sensitivity, estimating error rates of diagnostic tests, Applications of statistics to biology and medical sciences; meta analysis, conditional independence of errors, Humans, Diagnostic Errors, Tuberculosis, Pulmonary, Probability, Skin Tests
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