Table 1 Likelihood Ratios* Are Superior to SpPin and SnNout—an Illustrative Example

					Best test to rule in disease based on:†		Best test to rule out disease based on:†
Test	Sensitivity	Specificity	LR+ ‡	LR− §	SpPin‖	Highest posttest probability generated	SnNout¶	Lowest posttest probability generated
A	30%	95%	6.0	0.74	✓
B	95%	30%	1.4	0.17			✓
C	90%	90%	9.0	0.11		✓		✓

^*Likelihood ratio = probability of a given test result among those with disease / probability of the same test result among those without disease

^†The best test for ruling in disease is the one that can generate the highest posttest probability (due to having the result with the highest likelihood ratio), and the best test for ruling out disease is the one that can generate the lowest posttest probability (due to having the result with the lowest likelihood ratio). This is also true for tests with more than two possible results. Using SpPin and SnNout to judge which test is best results in the wrong answer

^‡LR+  = likelihood ratio for a positive test result = probability of a positive test among those with disease / probability of a positive test among those without disease = sensitivity / (100 − specificity)

^§LR−  = likelihood ratio for a negative test result = probability of a negative test among those with disease / probability of a negative test among those without disease = (100 − sensitivity) / specificity

‖SpPin = heuristic that indicates that when Specificity is high, a Positive result rules in the disease in question, which incorrectly implies that the test with the highest specificity, when positive, is the best test for ruling in disease

^¶SnNout = heuristic that indicates that when Sensitivity is high, a Negative result rules out the disease in question, which incorrectly implies that the test with the highest sensitivity, when negative, is the best test for ruling out disease