Comparing the accuracy of two diagnostic tests applied on the same sample

Hi there,

I have recently come across some data that compares the accuracy of two diagnostic tests. We have 214 samples which are tested positive using a "gold standard" test. Using diagnostic test A, 145 / 214 (67.8%) were tested positive, whereas using diagnostic B, 213 / 214 (99.5%) were tested positive. Out of the total of 214, only one sample was tested negative with both test A and B.

We have not used the two diagnostic tests on samples that were tested negative using the "gold standard" test.

I am a bit confused about what is correct statistical test to use here, but decided to vote against the following tests:
- Since both of these two percentages are drawn from the same sample, I cannot use a two-sample t test for percentage (the two samples are not independent of each other).
- I figured that I also cannot use a one-sample t test for percentage because the two percentages were not mutually exclusive of each other (i.e. as they add up to more than 100%).
- I considered using a Chi square test, but I don't think I could form an unbiased "expected" frequency here.

A bit more reading led me to consider the McNemar's test, which (to my understanding) allow repeated testing of the same sample. I put my numbers into GraphPad QuickCalc online and it gave me a p value < 0.0001. I am still unsure if I did the right thing; if anyone could confirm that McNemar's test was the correct test, or if not, suggest a better test to use, I would very very much appreciate it.

Thank you for your time in advance!


Less is more. Stay pure. Stay poor.
You never say it, but you are trying to compare the results from the two diagnostics on the same 214 patient sample, correct?


Less is more. Stay pure. Stay poor.
In my head mcnemar seems wrong since it is typically used on a 2x2 table that has a stratum variable. But you don't know how the diagnostic functioned on the negative tests so you have a 1x2 with a stratum.