Additional file 4 of Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case ...

Additional file 4: Table S1. Analyses of the potential predictors of spatial heterogeneity in hospitalisation incidence of nursing home (NH) residents. This table is equivalent to Table 1 and summarises the results of univariate linear regression (ULR), multivariate linear regression (MLR), and boosted regression trees (BRT) analyses performed to investigate the association between measures of hospitalisation incidence (HI) of NH residents and various spatial covariates associated with hospital catchment areas (HCAs). We report the following metrics: the coefficient of determination (R2) for t... Mehr ...

Verfasser: Dellicour, Simon
Linard, Catherine
Van Goethem, Nina
Da Re, Daniele
Artois, Jean
Bihin, Jérémie
Schaus, Pierre
Massonnet, François
Van Oyen, Herman
Vanwambeke, Sophie O.
Speybroeck, Niko
Gilbert, Marius
Dokumenttyp: Journal contribution
Erscheinungsdatum: 2021
Verlag/Hrsg.: figshare
Schlagwörter: Medicine / Biotechnology / 59999 Environmental Sciences not elsewhere classified / FOS: Earth and related environmental sciences / 69999 Biological Sciences not elsewhere classified / FOS: Biological sciences / 80699 Information Systems not elsewhere classified / FOS: Computer and information sciences / 19999 Mathematical Sciences not elsewhere classified / FOS: Mathematics / Cancer / Inorganic Chemistry / FOS: Chemical sciences / Plant Biology / Computational Biology
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-28970078
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://dx.doi.org/10.6084/m9.figshare.14782545.v1

Additional file 4: Table S1. Analyses of the potential predictors of spatial heterogeneity in hospitalisation incidence of nursing home (NH) residents. This table is equivalent to Table 1 and summarises the results of univariate linear regression (ULR), multivariate linear regression (MLR), and boosted regression trees (BRT) analyses performed to investigate the association between measures of hospitalisation incidence (HI) of NH residents and various spatial covariates associated with hospital catchment areas (HCAs). We report the following metrics: the coefficient of determination (R2) for the ULR analyses, the regression coefficient (β) for the MLR analyses, and the relative influence (RI) associated with each spatial covariate for the BRT analyses. In addition, we also report the overall R2 and Spearman correlation (“cor.”) for each distinct MLR and BRT analysis, respectively. (*) indicates if a given R2 or β is significant (p-value < 0.05). Table S2. Analyses of the potential predictors of spatial ...