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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.
A false positive Covid-19 test result can happen, but it’s rare, says Brian Labus, Ph.D., M.P.H., assistant professor at the University of Nevada Las Vegas School of Public Health.
The probability for false positives varies by each type of home test, but Ellume specifically says on its online FAQs that "there is a chance that this test can give a positive result that is ...
Accuracy is measured in terms of specificity and selectivity. Test errors can be false positives (the test is positive, but the virus is not present) or false negatives, (the test is negative, but the virus is present). [179] In a study of over 900,000 rapid antigen tests, false positives were found to occur at a rate of 0.05% or 1 in 2000. [180]
False positives can also produce serious and counter-intuitive problems when the condition being searched for is rare, as in screening. If a test has a false positive rate of one in ten thousand, but only one in a million samples (or people) is a true positive, most of the positives detected by that test will be false.
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.
Here "T+" or "T−" denote that the result of the test is positive or negative, respectively. Likewise, "D+" or "D−" denote that the disease is present or absent, respectively. So "true positives" are those that test positive (T+) and have the disease (D+), and "false positives" are those that test positive (T+) but do not have the disease (D ...