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Accounting for uncertainty during a pandemic.
Zelner, Jon; Riou, Julien; Etzioni, Ruth; Gelman, Andrew.
  • Zelner J; Department of Epidemiology, Center of Social Epidemiology & Population Health, University of Michigan School of Public Health, Ann Arbor, MI, USA.
  • Riou J; Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
  • Etzioni R; Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA, USA.
  • Gelman A; Department of Statistics and Department of Political Science, Columbia University, New York, NY, USA.
Patterns (N Y) ; 2(8): 100310, 2021 Aug 13.
Article in English | MEDLINE | ID: covidwho-1763926
ABSTRACT
We discuss several issues of statistical design, data collection, analysis, communication, and decision-making that have arisen in recent and ongoing coronavirus studies, focusing on tools for assessment and propagation of uncertainty. This paper does not purport to be a comprehensive survey of the research literature; rather, we use examples to illustrate statistical points that we think are important.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Patterns (N Y) Year: 2021 Document Type: Article Affiliation country: J.patter.2021.100310

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Patterns (N Y) Year: 2021 Document Type: Article Affiliation country: J.patter.2021.100310