He published an estimate of SARS-CoV-2 antibody seroprevalence in Santa Clara county, claiming a signal from a positivity rate that was within the 95% CI for th

He published an estimate of SARS-CoV-2 antibody seroprevalence in Santa Clara county, claiming a signal from a positivity rate that was within the 95% CI for the false-positive rate for the test. Recruitment was also highly non-random. 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... Such careless use of statistics is hardly uncommon; but it's funny to see that he succumbed too, perhaps blinded by the same factors he identifies in this paper. Beyond that, he sometimes advocated for a less restrictive response on the basis of predictions (of deaths, infections, etc.) that turned out to be incorrect. I don't think that's a conspiracy theory, though. Are the scientists who advocated for school closures now "conspiracy theorists" too, because they failed to predict the learning loss and social harm we now observe in those children? Any pandemic response comes with immense harms, which are near-impossible to predict or even articulate fully, let alone trade off in an unquestionably optimal way.