The two disease spectrums among the patients used to develop tests tend to be more severe than those of the typical clinical situation, meaning that test performance in practice is often lower than published estimates. Removing the test positives from a group changes the two disease spectrums, which is likely to adversely affect the performance of subsequent tests. For determining sensitivity and specificity of screening tests, the appropriate disease spectrums are those of a cross-section of an appropriate population, which are usually less severe than those of individuals being diagnosed in clinical settings. The mathematical relationship between the probability that an individual has the disease before the test is run to the probability that the individual has the disease after the test result is known. Baye's theorem essentially relates the certainty that the individual has a disease prior to doing the test, the two possible test results, and the certainty that the individual has the disease after doing the test.
False negatives are undesirable test outcomes as such individuals are missclassified.
False positives are undesirable test outcomes as such individuals are missclassified. An individual that is both test negative and disease negative. An individual that is both test positive and disease positive. For groups, sensitivity is the proportion of diseased individuals that will test positive. Raising a test's Se by changing its cutoff lowers the test's specificity.