A spatial model to jointly analyze self‐reported survey data of COVID‐19 symptoms and official COVID‐19 incidence data

DOI10.1002/bimj.202100186WikidataQ114698598 ScholiaQ114698598MaRDI QIDQ6149257

Christel Faes, Pierre Van Damme, Unnamed Author, Unnamed Author, Unnamed Author, Niel Hens, Philippe Beutels, Geert Molenberghs, Thomas Neyens, Unnamed Author

Publication date: 4 March 2024

Published in: Biometrical Journal (Search for Journal in Brave)

zbMATH Keywords

survey datapreferential samplingdisease mappingCOVID-19bivariate conditional autoregressive random effect

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

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• A family of generalized linear models for repeated measures with normal and conjugate random effects
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• Bayesian geostatistical modelling with informative sampling locations
• A Predictive Approach to Model Selection
• Applied Spatial Statistics for Public Health Data
• Order-Free Co-Regionalized Areal Data Models with Application to Multiple-Disease Mapping
• Disease Mapping

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