[M T]

In the section of the Stanford report on the statistical measurements of the accuracy of the test, they mention "Among 371 pre-COVID samples, 369 were negative."  But that's only for IgM.   For IgG, per the manufacturer, it is 368 were negative (3 positive).  I don't see that number (99.2%) being used in their calculations.

It appears to me that the study used the wrong specificity on the IgG part of the test.  They state "Similarly, our estimates of specificity are 99.5%(95 CI 98.1-99.9%)and 100%(95 CI 90.5-100%)."  I believe they mean that the specificity of the IgM test is 99.5% and the specificity of the IgG test is 100%.  However, the manufacturer  indicates that the IgG gave 3 false positives in 371 tests with IgG.   So I believe their methodology should use either the minimum 99.2% or (75+368)/(75+371) = 99.3% for the IgG specificity.

I'll leave it to the statisticians to calculate the overall specificity (and the confidence intervals) when either a positive IgG or IgM is counted as a positive.  I'm confident it is below the 99.5% used in the report.  (I think this only drops it to 99.4%, or about 20 false positives in 3330 tests, leaving a raw incidence of 0.1% in this population.)

[M T]

In the section of the Stanford report on the statistical measurements of the accuracy of the test, they mention "Among 371 pre-COVID samples, 369 were negative."  But that's only for IgM.   For IgG, per the manufacturer, it is 368 were negative (3 positive).  I don't see that number (99.2%) being used in their calculations.

It appears to me that the study used the wrong specificity on the IgG part of the test.  They state "Similarly, our estimates of specificity are 99.5%(95 CI 98.1-99.9%)and 100%(95 CI 90.5-100%)."  I believe they mean that the specificity of the IgM test is 99.5% and the specificity of the IgG test is 100%.  However, the manufacturer  indicates that the IgG gave 3 false positives in 371 tests with IgG.   So I believe their methodology should use either the minimum 99.2% or (75+368)/(75+371) = 99.3% for the IgG specificity.

I'll leave it to the statisticians to calculate the overall specificity (and the confidence intervals) when either a positive IgG or IgM is counted as a positive.  I'm confident it is below the 99.5% used in the report.  (I think this only drops it to 99.4%, or about 20 false positives in 3330 tests, leaving a raw incidence of 0.1% in this population.)