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Answer:
The positive predictive value ≈ 30.012%
Step-by-step explanation:
(a) The given percentage of the people in the region that have the disease, P(D) = 6% = 0.06
The percentage people correctly identified as having the disease by the standard diagnostic test = 91%
The percentage of people incorrectly identified as having the disease by the standard diagnostic test, P(T + |H) = 8%
Therefore, the sensitivity of the test, P(T + |D) = 0.91
The specificity of the test, P(T - |H) = 1 - 0.08 = 0.92
Therefore, the probability that a person is healthy, P(H) = 1 - 0.06 = 0.94
Therefore, in a population of 1,000 people, 60 people have the disease, with a sensitivity of 91%, the test will correctly pic 0.91×66 = 60.06 people correctly with the disease and 0.91 × 940 = 855.4 people without the disease
The number of non-diseased that test positive by the test is 0.08 × 1000 = 80 people which are false positives
Therefore, the number of diseased diagnosed as negative is 0.08 × 60 = 4.8
Therefore, we have;
The positive predictive value = Diseased +ve/(Diseased +ve + Non-diseased +ve)
Therefore;
The positive predictive value = 60.06/(60.06 + 140.06) × 100 ≈ 30.012%