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SBF
@SBF_FTX
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@SBF_FTX
4) Well, there's not much discussion of that! Because the core focus is that there's a *statistically significant* result, rather than how *important* that result is. That's stupid. The more important question is how large the effect is, not how large the study was!
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SBF
@SBF_FTX
5) In this case, it seems like the mandates decreased COVID in schools by ~20 cases per 100,000 children per week. That's ~0.02%/week, or ~1%/year. Would you rather: a) wear a mask for 100 years b) get COVID once I'll let you judge how the benefits compare to the costs.
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SBF
@SBF_FTX
6) But there's a second problem--it's not clear that those results are controlling for confounders. Now, the study did look at confounding variables! It's just, they first produced the chart, and *then* re-ran the numbers controlling. Or, at least, they imply so.
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SBF
@SBF_FTX
7) After controlling for "age, race and ethnicity, pediatric COVID-19 vaccination rate, COVID-19 community transmission, population density, social vulnerability index score, COVID-19 community vulnerability index score, percentage uninsured, and percentage living in poverty":
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SBF
@SBF_FTX
8) "school mask requirements remained associated with lower daily case rates of pediatric COVID-19 (β = −1.31; 95% confidence interval = −1.51 to −1.11) (p<0.001)." Without controlling, it's ~1%/year. After controlling, it's... P<0.001.
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SBF
@SBF_FTX
9) As far as I can tell, they don't actually say how large the effect was after controlling for confounding variables. They just clarify that it's still statistically significant--it could be massive, or it could be essentially 0. They don't report it!
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SBF
@SBF_FTX
10) Come on, guys. *Anything* is statistically significant if your study has enough participants. What matters is how large the effect is.
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