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A likelihood ratio of greater than 1 for a test in a population indicates that a positive test result is evidence that a condition is present. If the likelihood ratio for a test in a population is not clearly better than one, the test will not provide good evidence: the post-test probability will not be meaningfully different from the pretest ...
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
In the most basic sense, there are four possible outcomes for a COVID-19 test, whether it’s molecular PCR or rapid antigen: true positive, true negative, false positive, and false negative.
If you test negative using an at-home test, repeat the test again in 48 hours. If you were exposed to COVID, test at least 5 full days after exposure. If you still test negative, wait 48 more ...
Diagram relating pre- and post-test probabilities, with the green curve (upper left half) representing a positive test, and the red curve (lower right half) representing a negative test, for the case of 90% sensitivity and 90% specificity, corresponding to a likelihood ratio positive of 9, and a likelihood ratio negative of 0.111.
If you get two negative at-home COVID test results 48 hours apart after previously testing positive, you are likely no longer contagious. But how long that will take is "wholly dependent on the ...
The true positive in this figure is 6, and false negatives of 0 (because all positive condition is correctly predicted as positive). Therefore, the sensitivity is 100% (from 6 / (6 + 0) ). This situation is also illustrated in the previous figure where the dotted line is at position A (the left-hand side is predicted as negative by the model ...