b)
P(tested positive) =0.02*0.9975+0.98*0.0060 =0.0258
c)
sensitivity =0.9975
specificity=0.9940
positive predicted value =0.02*0.9975/0.0258=0.7724
Enzyme immunoassay tests are used to screen blood specimens for the presence of antibodies to HIV,...
Enzyme immunoassay tests are used to screen blood specimens for the presence of antibodies to HIV, the virus that causes AIDS. Antibodies indicate the presence of the virus. The test is quite accurate but is not always correct. Here are approximate probabilities of positive and negative test results when the blood tested does and does not actually contain antibodies to HIV: Test + Test - Antibodies present 0.9951 0.0049 Antibodies absent 0.0011 0.9989 For example, the top left cell gives...
Enzyme immunoassay (EIA) tests are used to screen blood specimens for the presence of antibodies to HIV, the virus that causes AIDS. Antibodies indicate the presence of the virus. The test is quite accurate but is not always correct. Suppose that 1% of a large population carries antibodies to HIV in their blood. Of those that carry the HIV antibodies in their blood, 99.85% will have a positive test result and 0.15% will have a false-negative test result. Of those...
3. The standard blood test screen for the Human Immunodeficiency Virus (HIV) detects antibodies to the virus using a laboratory test known as ELISA (enzyme-linked immunosorbent assay). If the ELISA test is run properly under recommended conditions, it has a sensitivity of 99% and a specificity of 99%. a) (4 pts) Assume the HIV-ELISA test is administered to a low-risk community of 100,000 people. By low-risk we mean a population which has an HIV prevalence of 1%. Construct the appropriate...
A test for the presence in the blood of antibodies to HIV, the virus that causes AIDS, gives a positive result with probability about 0.004 when a person who is free of HIV antibodies is tested. This is called a false positive. A clinic tests 5000 people who are all free of HIV antibodies. What is the probability that between 10 and 15 people in this sample will receive a false positive reading?
A test for the presence in the blood of antibodies to HIV, the virus that causes AIDS, gives a positive result with probability about 0.004 when a person who is free of HIV antibodies is tested. This is called a false positive. A clinic tests 5000 people who are all free of HIV antibodies. What is the probability that between 10 and 15 people in this sample will receive a false positive reading?
A rapid test for the presence in the blood of antibodies to HIV, the virus that causes AIDS, gives a positive result with probability about .004 when a person who is free of HIV antibodies is tested. A clinic tests 1000 people who are all free of HIV antibodies. a. what is the distribution of the number of positive tests? b. what is the mean number of positive tests? c. you cannot safely use the Normal approximation fr this distribution....
Medical screening tests are used to check for the presence on disease, evidence of illegal drug use, etc. The its sensitivity and its specificity. The sensitivity among those with the condition that will test positive. The specichy proportion among those without the condition that will test neg sensitivity of a test is defined to be the conditional ng those without the condition that will test negative. More formally, the test is defined to be the conditional probability that a person...
The DoubleCheckGoldTM HIV 1&2 test has a sensitivity of 99.9% and a specificity of 99.6%. Suppose that a particular high-risk population has an HIV prevalence of 10%. a. Suppose that a member of this high-risk population is known to be HIV positive. What is the probability that this person will produce a false negative result using this test? Report the result to the nearest tenth of a percent. b. Compute and interpret the positive predictive value for this test when...
Diagnostic tests of medical conditions can have several types of results. The test result can be positive or negative, whether or not a patient has the condition. A positive test (+) indicates that the patient has the condition. A negative test (-) indicates that the patient does not have the condition. Remember, a positive test does not prove the patient has the condition. Additional medical work may be required. Consider a random sample of 200 patients, some of whom have...
Condition Condition Present Absent Row Total Test Result + 110 130 Test Result - 20 50 70 Column Total 130 200 Assume the sample is representative of the entire population. For a person selected at random, compute the following probabilities: (a) P(+ condition present); this is known as the sensitivity of a test. (b) PC- I condition present); this is known as the false-negative rate. (c) P(- I condition absent); this is known as the specificity of a test. (d)...