4 ms·

If you read that recent random sampling from Stanford the numbers are probably 50x-85x higher

andylei 7y ago
isn't this also random sampling?
obastani 7y ago
The result in the Stanford paper is very likely biased due to the false positive rate of the test they used: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...
- rvnx 7y ago
  and the FB data is likely underestimated too, because many persons don't feel comfortable about answering honestly with their real name to a company/university that could be coerced by government to share their identity (and that could mean fines, jail, or quarantine)
- DeonPenny 7y ago
  But thats a better percentage than a lot of the normal covid tests. I haven't done the math entirely but a 98.3% to 99.9% accurate test doesn't seem to correlate with a 50x-85x jump. If anyone can write out the proof that would be great. Also this article has one weird thing I picked up on and maybe I someone can verify it but they've said 100 people died in Santa Clara country but I could find 73 possible covid-19 deaths. All of those haven't been verified. This is based on April 17th numbers
  - dumbfoundded 7y ago
    I don't know the specific numbers but this jump is definitely possible. Let's say the false-negative rate is 0% and the false-positive rate is 2%. For sake of argument, let's say that 0.05% actually have Covid. If you tested 10000, 5 people have it in reality but your testing would show that 205 people tested positive.
    - DeonPenny 7y ago
      That doesn't seem right if it says 5 people had it then a false positive would only say that there's a 2% that likelihood that that test is wrong. Its not saying there is a 2% likelihood that 10000 people are sick. Its saying there's a 98% chance that this test diagnosis them right and 2% chance it does it wrong. This is better than the false positive of other tests like the normal tests with a 10-15% false positive rate. https://abc7news.com/coronavirus-test-free-testing-update-accuracy/6053940/ https://abc7news.com/coronavirus-test-free-testing-update-ac... Also this
- DeonPenny 7y ago
  I've found that the false postive rate of the normal test to be 10% and chest CT to 6%. https://abc7news.com/coronavirus-test-free-testing-update-accuracy/6053940/ https://abc7news.com/coronavirus-test-free-testing-update-ac.... Shouldn't we use this simply because the false positive of 2%-1% is lower than those tests we are using for making policies right now.
wbronitsky 7y ago
The sampling was not random; they got their participants from a Facebook ad. https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1 https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v...
- SpicyLemonZest 7y ago
  So, about as random as this Facebook survey then?
  - wbronitsky 7y ago
    Yes, in that neither of them are random
  - justapassenger 7y ago
    No idea if Facebook did that, but they do know demographic profile of responders, so they could correct data to make it more stat sig.
  - pedrosorio 7y ago
    The people who chose to respond to this ad were probably a very biased sample of the population: https://twitter.com/foxjust/status/1251270848075440133/photo/1 https://twitter.com/foxjust/status/1251270848075440133/photo...
SpicyLemonZest 7y ago
They appear to be trying to estimate the percentage who had symptoms at the time of the survey date, while the Stanford study was estimating the percentage who've had the virus (even if asymptomatic) at any time in the past.
zaidf 7y ago
Stanford should completely retract that study. It has produced far more misleading interpretations than anything useful.
- timr 7y ago
  There was nothing wrong with that study that wasn't already acknowledged in the study itself. No study is perfect. If the bar for retraction of a paper is that people are misinterpreting it, then most of the studies on masks should be retracted as well.
- DeonPenny 7y ago
  I don't think they've interpreted anything. It falls in line with other random sampling tests. Without this data we could be making the wrong decision. Especially with countries doing widely different things. Places like Sweden, Korea, and Taiwan without quarantine and places like Germany or the US with quarantine should know which strategy works best. Which isn't at all clear right now.
- ravenstine 7y ago
  Why? Even if it's not totally random(they used Facebook ads), surely the data still tells us something?
  - losvedir 7y ago
    Not necessarily. Their population survey had 1.5% positive results. The false positive rate of the test is not known for certain but I believe the 95% confidence interval goes up to 1.7%. If that were the case, all the positive tests could even be false positives. We did learn from the study that the population rate isn't outrageously high, like 30%, but I'm not sure what more we can confidently say beyond that.
    - walterbell 7y ago
      What are typical false positive rates for other tests/studies?
deleted 7y ago
[deleted]

isn't this also random sampling?

The result in the Stanford paper is very likely biased due to the false positive rate of the test they used: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/ https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaw...

rvnx 7y ago
and the FB data is likely underestimated too, because many persons don't feel comfortable about answering honestly with their real name to a company/university that could be coerced by government to share their identity (and that could mean fines, jail, or quarantine)
DeonPenny 7y ago
But thats a better percentage than a lot of the normal covid tests. I haven't done the math entirely but a 98.3% to 99.9% accurate test doesn't seem to correlate with a 50x-85x jump. If anyone can write out the proof that would be great. Also this article has one weird thing I picked up on and maybe I someone can verify it but they've said 100 people died in Santa Clara country but I could find 73 possible covid-19 deaths. All of those haven't been verified. This is based on April 17th numbers
- dumbfoundded 7y ago
  I don't know the specific numbers but this jump is definitely possible. Let's say the false-negative rate is 0% and the false-positive rate is 2%. For sake of argument, let's say that 0.05% actually have Covid. If you tested 10000, 5 people have it in reality but your testing would show that 205 people tested positive.
  - DeonPenny 7y ago
    That doesn't seem right if it says 5 people had it then a false positive would only say that there's a 2% that likelihood that that test is wrong. Its not saying there is a 2% likelihood that 10000 people are sick. Its saying there's a 98% chance that this test diagnosis them right and 2% chance it does it wrong. This is better than the false positive of other tests like the normal tests with a 10-15% false positive rate. https://abc7news.com/coronavirus-test-free-testing-update-accuracy/6053940/ https://abc7news.com/coronavirus-test-free-testing-update-ac... Also this
DeonPenny 7y ago
I've found that the false postive rate of the normal test to be 10% and chest CT to 6%. https://abc7news.com/coronavirus-test-free-testing-update-accuracy/6053940/ https://abc7news.com/coronavirus-test-free-testing-update-ac.... Shouldn't we use this simply because the false positive of 2%-1% is lower than those tests we are using for making policies right now.

wbronitsky 7y ago

The sampling was not random; they got their participants from a Facebook ad. https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1 https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v...

SpicyLemonZest 7y ago
So, about as random as this Facebook survey then?
- wbronitsky 7y ago
  Yes, in that neither of them are random
- justapassenger 7y ago
  No idea if Facebook did that, but they do know demographic profile of responders, so they could correct data to make it more stat sig.
- pedrosorio 7y ago
  The people who chose to respond to this ad were probably a very biased sample of the population: https://twitter.com/foxjust/status/1251270848075440133/photo/1 https://twitter.com/foxjust/status/1251270848075440133/photo...

SpicyLemonZest 7y ago

They appear to be trying to estimate the percentage who had symptoms at the time of the survey date, while the Stanford study was estimating the percentage who've had the virus (even if asymptomatic) at any time in the past.

zaidf 7y ago

Stanford should completely retract that study. It has produced far more misleading interpretations than anything useful.

timr 7y ago
There was nothing wrong with that study that wasn't already acknowledged in the study itself. No study is perfect. If the bar for retraction of a paper is that people are misinterpreting it, then most of the studies on masks should be retracted as well.
DeonPenny 7y ago
I don't think they've interpreted anything. It falls in line with other random sampling tests. Without this data we could be making the wrong decision. Especially with countries doing widely different things. Places like Sweden, Korea, and Taiwan without quarantine and places like Germany or the US with quarantine should know which strategy works best. Which isn't at all clear right now.
ravenstine 7y ago
Why? Even if it's not totally random(they used Facebook ads), surely the data still tells us something?
- losvedir 7y ago
  Not necessarily. Their population survey had 1.5% positive results. The false positive rate of the test is not known for certain but I believe the 95% confidence interval goes up to 1.7%. If that were the case, all the positive tests could even be false positives. We did learn from the study that the population rate isn't outrageously high, like 30%, but I'm not sure what more we can confidently say beyond that.
  - walterbell 7y ago
    What are typical false positive rates for other tests/studies?

deleted 7y ago

[deleted]