BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic

Abstract

We developed a generative model for key epidemiological events in COVID-19 patients and derived explicit formulae to correct for selection bias. We find that several early analyses of the COVID-19 pandemic were severely biased due to sample selection.

Publication
Annals of Applied Statistics (2021)
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