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A systematic review of statistical model selection techniques used to predict COVID-19 health outcomes

Year: 2025

Type: conference-paper

Abstract: Background: Following the outbreak of the Covid-19 pandemic, the scientific community rapidly developed models to predict health outcomes. The Strengthening Analytical Thinking for Observational Studies (STRATOS) initiative's Topic Group 2 (TG2) ‘selection of variables and functional forms [for full text, please go to the a.m. URL]

Source: German Medical Science (German Research Foundation)

DOI: 10.3205/25gmds094

Authors: Buch, Gregor, Kammer, Michael, Henrion, Marc, Heinze, Georg, TG2 of the STRATOS initiative

Institutions: Johannes Gutenberg University Mainz, University Medical Center of the Johannes Gutenberg University Mainz, Medical University of Vienna, Liverpool School of Tropical Medicine, Malawi-Liverpool-Wellcome Trust Clinical Research Programme

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7103900334

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