re: Antibodies ...why are they not getting any love?

quote:

---

Are you suggesting Stanford docs are running bad studies?

---

Yes, this study was conducted poorly. Did you read it?

From the report itself:

quote:

---

This study has several limitations. The primary limitation concerns sample selection biases. Our sample
may be enriched with COVID-19 participants, by selecting for individuals with a belief or curiosity
concerning past infection. We discuss further and attempt to quantify the potential impact of this bias in
the Additional Data and Response to Comments section. Our study may also have selected for groups of
people more likely to skew our sample against COVID-19 participants. For example, our sample strategy
selected for members of Santa Clara County with ready access to Facebook who viewed our
advertisement early after the registration opened. Our sample ended up with an over-representation of
white women between the ages of 19 and 64, and an under-representation of Hispanic and Asian
populations, relative to our community. Those imbalances were partly addressed by weighting our sample
by zip code, race, and sex to match the county. Our survey also selected for members of the population
who were able to spare the time to drive to the testing site, which may have skewed our sample against
essential workers. Our study was also limited in that it could not ascertain representativeness of SARSCoV-2 antibodies in other communities with possibly high prevalence, such as homeless populations and
nursing homes. The overall direction and magnitude of these selection effects are hard to fully bound, and
our estimates reflect the prevalence in our sample, weighted to match county demographics.

---

Translated: "The sample self-selected, and this introduces many possible biases. We have guessed which biases are present in the sample and weighted the data until it looked good to us."

Also, check out the ethnicity of the sample and their respective raw prevalences:

quote:

---

White 2,118 1.0
Asian 623 1.9
Hispanic 266 4.9
Other 306 1.3
Total 3,313* 1.5

---

Only 8% of the sample was hispanic, but they make up 26% of the county. Nearly 5% of the hispanics in the sample tested positive, a clear outlier vs. the rest of the ethnicities. And whites made up 64% of the sample, but are only 33% of the population. Only 1% of whites tested positive. No problem, just weight them properly, right? Well, the result of that is hispanics were multiplied by 3, and whites were cut in half. That means if an hispanic was a false positive, it would have roughly 6X as much impact in the results vs. if a white person was a false positive.

They detail the methods used to account for all the problems with the sample, but when the sample is this bad, the adjustments can potentially make the results worse. There is a lot of guesswork here.

And we haven't even gotten to the accuracy of the tests, which is not only not great, but it's not even accurately know how not great they are.