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Zach H
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Statistical Modeling blog commenter on virology, Bayesian analysis, and COVID-19 origins
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covid-19-origins (3)
flf-epistack (3)
health (3)
public-health (3)
research-policy (3)
disinformation (2)
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Zach H
votes For
and says:
Instead of a Bayes factor of 0.25, we get a Bayes factor of 11.95 because one reasonable model (early cases predict locations of subsequent cases) is compared to an unreasonable model (everyone is infected by raccoon dogs).
AI Verified source (Feb 5, 2025)
added 20d ago
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The clustering of early cases around the Huanan market reflects where the COVID-19 virus emerged, not just where testing looked
273 opinions
Zach H
votes Against
and says:
Instead of a Bayes factor of 0.25, we get a Bayes factor of 11.95 because one reasonable model (early cases predict locations of subsequent cases) is compared to an unreasonable model (everyone is infected by raccoon dogs).
AI Verified source (Feb 5, 2025)
added 20d ago
-
Zach H
votes For
and says:
Instead of a Bayes factor of 0.25, we get a Bayes factor of 11.95 because one reasonable model (early cases predict locations of subsequent cases) is compared to an unreasonable model (everyone is infected by raccoon dogs).
AI Verified source (Feb 5, 2025)
added 20d ago