| > it sounds like you think I'm saying false negatives are the inverse of false positives? Not at all, that's obviously not true. No, I think you're saying that the false negative rate as I defined it in my comment is the inverse of sensitivity. You've corrected me to say that you think the rate I defined is the inverse of specificity, which makes even less sense. And you did that despite the fact that I included a full calculation demonstrating that that isn't true. Wikipedia's definition of the false negative rate differs from mine. Wikipedia indeed defines the false negative rate as (1 - sensitivity), though not, as you seem to believe, (1 - specificity). But you get no credit for this, because I explicitly defined what I meant by the false negative rate, and you echoed that definition in your response to my comment: >>> your changed-order definitions So: you think you haven't misunderstood what's happening. I ask you this: in my table above, I believe that prevalence is 20%, sensitivity is 95%, and specificity is 90%. Please verify that. I have said that the conditional probability P(condition present | test negative) is 1.4%. You responded saying that that probability is actually 10%: >> You have proposed that when the test says "no", the answer is "yes" a share of the time that might be the inverse of 5%, or perhaps 5% itself. > 10% Where are you getting that figure from? Show me in the table. |
(Though it does seem a little odd to me to object to the comment on the basis of a definition you introduce yourself that even if some sort of standard is something that varies enough that Wikipedia uses a crucially different one.)