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But the accuracy at an individual level will remain the same
The "accuracy" of the test remains the same but the accuracy of the result depends on your likelihood of having the thing in the first place.
This is because there are really 4 results: positive, false positive, negative, false negative. The proportion of positives that are false becomes relatively more or less important when compared with the proportion of results that are true positives.
If I, a biological male, take a pregnancy test with a 5% false positive rate, that doesn't mean that my chances of actually being pregnant are 5% - they are in effect 0% and all positives results are false positives. But the test is still correct 95% of the time.
Edit: I don't think my comment is going to help you, I'm just restating what you've already said.
frankenbike-
Absolutely. Agree with all of that.
But the part I'm trying to decipher follows from this: The accuracy of a pregnancy test does not change depending on how many women are currently pregnant.
What does change is the raw number of positive and negative results due to there being more people who can get false negatives. But any given man or woman will still have the same likelihood of getting a particular result.
Which is why you have a test/sample group. That's the population for which you know the number of false positives, false negatives, true positives, and true negatives. That's the population from which the accuracy of a test can be calculated.
Extrapolation to the world becomes more complicated. The prevalence in the population will impact raw results. But the accuracy at an individual level will remain the same (within reason/whatever p value).
As far as I understand! Not a doctor! Etc!