Likelihood ratios offer important advantages over sensitivity and specificity for characterizing diagnostic tests. They can capture the magnitude of abnormality of test results, whereas sensitivity and specificity require that the test results be dichotomized into positive or negative. This is an important advantage because many diagnostic tests are measured on continuous or ordinal scales. Posttest probabilities calculated from interval likelihood ratios may be different than those calculated from sensitivity and specificity; clinical decisions derived from the use of likelihood ratios may therefore be different from decisions derived from test results characterized by sensitivity and specificity. This article demonstrates the advantages, use, and interpretation of interval likelihood ratios using the clinical scenario of a young child with a high fever.