Bayesian and Nonparametric Statistics - Teaming up two opposing theories for the benefit of prognostic studies in Covid-19
- Funded by Volkswagen Stiftung
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19start year
2020Funder
Volkswagen StiftungPrincipal Investigator
Prof Dr and Prof Dr and Prof Dr Tim Friede, Frank Konietschke, Markus PaulyResearch Location
GermanyLead Research Institution
Universitätsmedizin Göttingen Georg August UniversitätResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease susceptibility
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
Unspecified
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
The main goal of this project is to consider how to avoid false conclusions from small single-center clinical studies in COVID-19 pandemic. By fusing Bayesian and non-parametric approaches, accurate prognosis with robust assessment of risk uncertainty to guide patient care and societal policies should be achieved.