Question

A certain disease has an incidence rate of 0.4%. If the false negative rate is 8% and the false positive rate is 2%, compute the probability that a person who tests positive actually has the disease

Answer 1

To compute the probability that a person who tests positive actually has the disease, we need to use Bayes' theorem:

P(D|P) = P(P|D) * P(D) / P(P)

where:

P(D|P) is the probability of having the disease given a positive test result

P(P|D) is the probability of testing positive given that the person has the disease (also known as sensitivity), which is 1 - false negative rate = 0.92 in this case

P(D) is the incidence rate of the disease, which is 0.4% = 0.004

P(P) is the probability of testing positive, which can be computed using the false positive rate as 1 - specificity = 1 - 0.98 = 0.02

Plugging in the values, we get:

P(D|P) = 0.92 * 0.004 / 0.02 = 0.184

Therefore, the probability that a person who tests positive actually has the disease is 0.184, or about 18.4%.