A test yields 80% infected and 10% non-infected.....prevalence is 10%.
What is positive predictive value?
A. 47%
B. 54%
C. 75%
D. 25%
What is positive predictive value?
A. 47%
B. 54%
C. 75%
D. 25%
very confusing question!Question:
A test yields 80% infected and 10% noninfected.....prevalence is 10%
...what is positive predicted value ??
a.47%
b.54%
c.75%
d.25%
BUT same question how specificity is 90% ?Imagine that population consist of 100 patients .Since the disease prevalence is 10% that means 10 patients have disease and 90 do not ..Performing a test with with 80% sensiitivity on 10 diseased patients yields 8 TF . performing a test with 90% specificity on 90patients without disease yield 9 FP ..
PPV = 8/(8+9) = 47%
Got itAnswer is:
BUT same question how specificity is 90% ?
but how do we know that 10 percent were labeled as false positive...Seems like I guessed correctlywhat medicalbiology was trying to say in the first post.
Here's how I had gotten around it.
Thank you soo much!! Great explanationLets say sample size is 1000 patients
Prevalance = 30%
Therefore diseased = 300, non diseased = 700
We now need to work out our TP and FP numbers
Sensitivity = 45% In other words this test will give a positive result in 45% of the people with the disease (ie its rubbish!)
So the True Positive rate = 300 x 45% = 135.
This means that the False Negative rate, which is all the patients our test missed, is 300 - 135 = 165
Now, specificity = 45%
This means that, out of all the 700 patients without disease, our test will give a truly negative result only 45% of the time
So our True Negative rate = 700 x 45% = 315
This means that the False Positive rate, which is all the patients without disease that our test gave a positive result for, is 700 - 315 = 385
We now have all the numbers needed to make a 4x4 table and work out anything else.
The PPV = TP/(TP+FP) = 135/(135+385) = 26%
So the test is worse than simply tossing a coin...