The following two tables were provided to you as part of this week’s lecture, part 2. In each table:
Disease + means that a patient had a disease, as measured by a “gold standard” assessment
Disease – means that the patient did not have a disease, as measured by the gold standard
Test + means that the patient was classified as being positive for the disease according to a new test
Test – means that the patient was classified as being negative for the disease according to a new test
Table 1
Disease + |
Disease - |
Total |
|
Test + |
160 |
360 |
520 |
Test - |
40 |
1440 |
1480 |
Total |
200 |
1800 |
2000 |
Table 2 |
|||
Disease + |
Disease - |
Total |
|
Test + |
144 |
36 |
180 |
Test - |
16 |
324 |
340 |
Total |
160 |
360 |
520 |
Task 1: Using the measures described in Part 2 of the lecture (sensitivity, specificity, validity, and yield), describe the accuracy of the test to detect the presence of disease for the data described in Tables 1 and 2.
The sensitivity of a test is also called the true positive rate (TPR) and is the proportion of samples that are genuinely positive that give a positive result using the test in question. For example, a test that correctly identifies all positive samples in a panel is very sensitive.Hence the test given is not sensitive and all the positive results will not be reliable.
Specificity relates to the test's ability to correctly reject healthy patients without a condition.Specificity of a test is the proportion of healthy patients known not to have the disease, who will test negative for it.So the test has specificity.
Validity is the extent to which a concept, conclusion or measurement is well-founded and likely corresponds accurately to the real world.
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