sbryant6SPin and SNout. Specificity in, sensitivity out.+2019-07-14T02:20:19Z
link981Excellent explanation but a minor typo. 1-0.99 = 0.01 not 0.10 :)+12019-07-03T02:12:20Z
briseThe question is asking what point would be the most likely to rule in cancer, and high specificity when positive rules in cancer. The highest specificity value is A, bc the the X axis shows (1-specificity)!+42019-06-02T23:59:17Z
hellobrise is correct. Knowing the LR+ value = 10 does not help in this situation because estimating where "10" should fall on an axis is arbitrary.
The way to approach this Q is to know that a high specificity is will mean that a positive result is very very likely to be a true positive. In theory, suppose that the specificity was 0.99. This is 99% specificity. Then, you look at the graph. The X-axis is "1-specificity." So, suppose the best test has a specificity of 99%. Then, calculating 1-specificity = 1 - 0.99 = 0.1. You would then chose the datapoint that corresponds to having an "X-value" that is closest to the origin. In this problem, it corresponds to data point "A."+22019-06-11T22:12:32Z