definitional legerdemain, do not count the boosted as boosted, el gato malo, misallocated cases, mishandle the cohort sizes, stats as misinformation, stats as propaganda, stats with cats, virtual outright datacrime
Source: bad cattitude
this issue around dropping the two risk enhanced weeks has been with us from the beginning. it was baked into the drug trials as well and folks like pfizer do not make mistakes about issues like this, they make choices.— el gato malo
bayesian datacrime: defining vaccine efficacy into existence
how the definitions of “full vaccinated” and now “boosted” are exaggerating (and possibly creating from whole cloth) VE and turning the data into gibberish
welcome to another edition of “stats with cats.”
today’s topic: how to use definitional legerdemain to make products look like they work, taint data, and fool the unwary.
let’s start in highly vaccinated iceland where, despite ~80% vaccination rates and over 50% of the population boosted, cases are literally exploding.
testing roughly doubled, but this is still a DRAMATIC move even adjusted for sample rate.
many have argued that vaccines are helping. this data makes it look like they are not. the vaccinated are getting covid at something like twice the rate of the unvaxxed.
but, one might argue, this DOES make it look like boosters work. but this is not so either and that’s what i’d like to dig into.
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