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 & end 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 studiesResearch Subcategory
Disease susceptibilitySpecial Interest Tags
N/AStudy Type
Non-ClinicalClinical Trial Details
UnspecifiedBroad Policy Alignment
PendingAge Group
Not ApplicableVulnerable Population
Not applicableOccupations 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.